Eric03 commited on
Commit
c002491
·
verified ·
1 Parent(s): e8edd23

Add files using upload-large-folder tool

Browse files
This view is limited to 50 files because it contains too many changes.   See raw diff
Files changed (50) hide show
  1. 2002.01612/record.json +32 -0
  2. 2004.09411/record.json +32 -0
  3. 2005.00316/record.json +32 -0
  4. 2006.04016/record.json +32 -0
  5. 2006.05580/record.json +32 -0
  6. 2006.09447/record.json +32 -0
  7. 2012.09446/record.json +32 -0
  8. 2101.06969/record.json +32 -0
  9. 2101.08165/record.json +32 -0
  10. 2103.17242/record.json +32 -0
  11. 2104.08253/record.json +32 -0
  12. 2104.12437/record.json +32 -0
  13. 2106.00524/record.json +32 -0
  14. 2106.00985/record.json +32 -0
  15. 2106.01532/record.json +32 -0
  16. 2106.05321/record.json +32 -0
  17. 2106.05409/record.json +32 -0
  18. 2109.04284/record.json +32 -0
  19. 2109.08303/record.json +32 -0
  20. 2110.03868/record.json +32 -0
  21. 2111.02827/record.json +32 -0
  22. 2111.10361/record.json +32 -0
  23. 2112.01832/record.json +32 -0
  24. 2201.01928/record.json +32 -0
  25. 2201.06931/record.json +32 -0
  26. 2201.10649/record.json +32 -0
  27. 2201.12438/record.json +32 -0
  28. 2202.00063/record.json +32 -0
  29. 2202.06053/record.json +32 -0
  30. 2203.07259/record.json +32 -0
  31. 2203.10344/record.json +32 -0
  32. 2203.10428/record.json +32 -0
  33. 2203.12121/record.json +32 -0
  34. 2204.10358/record.json +32 -0
  35. 2204.11910/record.json +32 -0
  36. 2204.12322/record.json +32 -0
  37. 2205.02031/record.json +32 -0
  38. 2206.00067/record.json +32 -0
  39. 2206.00477/record.json +32 -0
  40. 2206.00843/record.json +32 -0
  41. 2206.03674/record.json +32 -0
  42. 2206.08460/record.json +32 -0
  43. 2206.13606/record.json +32 -0
  44. 2207.04873/record.json +32 -0
  45. 2207.06148/record.json +32 -0
  46. 2207.08664/record.json +32 -0
  47. 2207.10141/record.json +32 -0
  48. 2208.12212/record.json +32 -0
  49. 2209.06970/record.json +32 -0
  50. 2211.02127/record.json +32 -0
2002.01612/record.json ADDED
@@ -0,0 +1,32 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "arxiv_id": "2002.01612",
3
+ "month": "2020_02",
4
+ "year": 2020,
5
+ "conference": "IJCAI",
6
+ "title": "Generating Interpretable Poverty Maps using Object Detection in Satellite Images",
7
+ "arxiv_url": "https://arxiv.org/abs/2002.01612",
8
+ "source": {
9
+ "paper_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2020_02/main_diagram_database/2002.01612",
10
+ "tex_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2020_02/tex_files_extracted/2002.01612",
11
+ "paper_md": "/home/zling/lzl/ICML2026/Build_Dataset/data/2020_02/main_diagram_database/2002.01612/paper_text/paper.md",
12
+ "metadata_json": "/home/zling/lzl/ICML2026/Build_Dataset/data/2020_02/main_diagram_database/2002.01612/metadata.json",
13
+ "intro_method_from": "/home/zling/lzl/ICML2026/Build_Dataset/data/2020_02/main_diagram_database/2002.01612/paper_text/paper.md",
14
+ "intro_method_from_kind": "markdown"
15
+ },
16
+ "files": {
17
+ "main_drawio": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2002.01612/main_diagram/main_diagram.drawio",
18
+ "main_png": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2002.01612/main_diagram/main_diagram.png",
19
+ "main_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2002.01612/main_diagram/main_diagram.pdf",
20
+ "intro_method_md": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2002.01612/paper_text/intro_method.md",
21
+ "paper_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2002.01612/paper.pdf",
22
+ "latex": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2002.01612/latex_source"
23
+ },
24
+ "status": {
25
+ "copy_drawio": "exists",
26
+ "copy_png": "exists",
27
+ "diagram_pdf": "pdf_exists",
28
+ "intro_method": "exists",
29
+ "paper_pdf": "exists",
30
+ "latex": "exists"
31
+ }
32
+ }
2004.09411/record.json ADDED
@@ -0,0 +1,32 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "arxiv_id": "2004.09411",
3
+ "month": "2020_04",
4
+ "year": 2020,
5
+ "conference": "AAAI",
6
+ "title": "Shape-Oriented Convolution Neural Network for Point Cloud Analysis",
7
+ "arxiv_url": "https://arxiv.org/abs/2004.09411",
8
+ "source": {
9
+ "paper_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2020_04/main_diagram_database/2004.09411",
10
+ "tex_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2020_04/tex_files_extracted/2004.09411",
11
+ "paper_md": "/home/zling/lzl/ICML2026/Build_Dataset/data/2020_04/main_diagram_database/2004.09411/paper_text/paper.md",
12
+ "metadata_json": "/home/zling/lzl/ICML2026/Build_Dataset/data/2020_04/main_diagram_database/2004.09411/metadata.json",
13
+ "intro_method_from": "/home/zling/lzl/ICML2026/Build_Dataset/data/2020_04/main_diagram_database/2004.09411/paper_text/paper.md",
14
+ "intro_method_from_kind": "markdown"
15
+ },
16
+ "files": {
17
+ "main_drawio": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2004.09411/main_diagram/main_diagram.drawio",
18
+ "main_png": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2004.09411/main_diagram/main_diagram.png",
19
+ "main_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2004.09411/main_diagram/main_diagram.pdf",
20
+ "intro_method_md": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2004.09411/paper_text/intro_method.md",
21
+ "paper_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2004.09411/paper.pdf",
22
+ "latex": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2004.09411/latex_source"
23
+ },
24
+ "status": {
25
+ "copy_drawio": "exists",
26
+ "copy_png": "exists",
27
+ "diagram_pdf": "pdf_exists",
28
+ "intro_method": "exists",
29
+ "paper_pdf": "exists",
30
+ "latex": "exists"
31
+ }
32
+ }
2005.00316/record.json ADDED
@@ -0,0 +1,32 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "arxiv_id": "2005.00316",
3
+ "month": "2020_05",
4
+ "year": 2020,
5
+ "conference": "EMNLP",
6
+ "title": "Self-Supervised Knowledge Triplet Learning for Zero-Shot Question Answering",
7
+ "arxiv_url": "https://arxiv.org/abs/2005.00316",
8
+ "source": {
9
+ "paper_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2020_05/main_diagram_database/2005.00316",
10
+ "tex_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2020_05/tex_files_extracted/2005.00316",
11
+ "paper_md": "/home/zling/lzl/ICML2026/Build_Dataset/data/2020_05/main_diagram_database/2005.00316/paper_text/paper.md",
12
+ "metadata_json": "/home/zling/lzl/ICML2026/Build_Dataset/data/2020_05/main_diagram_database/2005.00316/metadata.json",
13
+ "intro_method_from": "/home/zling/lzl/ICML2026/Build_Dataset/data/2020_05/main_diagram_database/2005.00316/paper_text/paper.md",
14
+ "intro_method_from_kind": "markdown"
15
+ },
16
+ "files": {
17
+ "main_drawio": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2005.00316/main_diagram/main_diagram.drawio",
18
+ "main_png": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2005.00316/main_diagram/main_diagram.png",
19
+ "main_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2005.00316/main_diagram/main_diagram.pdf",
20
+ "intro_method_md": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2005.00316/paper_text/intro_method.md",
21
+ "paper_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2005.00316/paper.pdf",
22
+ "latex": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2005.00316/latex_source"
23
+ },
24
+ "status": {
25
+ "copy_drawio": "exists",
26
+ "copy_png": "exists",
27
+ "diagram_pdf": "pdf_exists",
28
+ "intro_method": "exists",
29
+ "paper_pdf": "exists",
30
+ "latex": "exists"
31
+ }
32
+ }
2006.04016/record.json ADDED
@@ -0,0 +1,32 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "arxiv_id": "2006.04016",
3
+ "month": "2020_06",
4
+ "year": 2020,
5
+ "conference": "ACL",
6
+ "title": "A Multitask Learning Approach for Diacritic Restoration",
7
+ "arxiv_url": "https://arxiv.org/abs/2006.04016",
8
+ "source": {
9
+ "paper_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2020_06/main_diagram_database/2006.04016",
10
+ "tex_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2020_06/tex_files_extracted/2006.04016",
11
+ "paper_md": "/home/zling/lzl/ICML2026/Build_Dataset/data/2020_06/main_diagram_database/2006.04016/paper_text/paper.md",
12
+ "metadata_json": "/home/zling/lzl/ICML2026/Build_Dataset/data/2020_06/main_diagram_database/2006.04016/metadata.json",
13
+ "intro_method_from": "/home/zling/lzl/ICML2026/Build_Dataset/data/2020_06/main_diagram_database/2006.04016/paper_text/paper.md",
14
+ "intro_method_from_kind": "markdown"
15
+ },
16
+ "files": {
17
+ "main_drawio": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2006.04016/main_diagram/main_diagram.drawio",
18
+ "main_png": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2006.04016/main_diagram/main_diagram.png",
19
+ "main_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2006.04016/main_diagram/main_diagram.pdf",
20
+ "intro_method_md": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2006.04016/paper_text/intro_method.md",
21
+ "paper_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2006.04016/paper.pdf",
22
+ "latex": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2006.04016/latex_source"
23
+ },
24
+ "status": {
25
+ "copy_drawio": "exists",
26
+ "copy_png": "exists",
27
+ "diagram_pdf": "pdf_exists",
28
+ "intro_method": "exists",
29
+ "paper_pdf": "exists",
30
+ "latex": "exists"
31
+ }
32
+ }
2006.05580/record.json ADDED
@@ -0,0 +1,32 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "arxiv_id": "2006.05580",
3
+ "month": "2020_06",
4
+ "year": 2020,
5
+ "conference": "CVPR",
6
+ "title": "Syn2Real Transfer Learning for Image Deraining Using Gaussian Processes",
7
+ "arxiv_url": "https://arxiv.org/abs/2006.05580",
8
+ "source": {
9
+ "paper_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2020_06/main_diagram_database/2006.05580",
10
+ "tex_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2020_06/tex_files_extracted/2006.05580",
11
+ "paper_md": "/home/zling/lzl/ICML2026/Build_Dataset/data/2020_06/main_diagram_database/2006.05580/paper_text/paper.md",
12
+ "metadata_json": "/home/zling/lzl/ICML2026/Build_Dataset/data/2020_06/main_diagram_database/2006.05580/metadata.json",
13
+ "intro_method_from": "/home/zling/lzl/ICML2026/Build_Dataset/data/2020_06/main_diagram_database/2006.05580/paper_text/paper.md",
14
+ "intro_method_from_kind": "markdown"
15
+ },
16
+ "files": {
17
+ "main_drawio": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2006.05580/main_diagram/main_diagram.drawio",
18
+ "main_png": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2006.05580/main_diagram/main_diagram.png",
19
+ "main_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2006.05580/main_diagram/main_diagram.pdf",
20
+ "intro_method_md": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2006.05580/paper_text/intro_method.md",
21
+ "paper_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2006.05580/paper.pdf",
22
+ "latex": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2006.05580/latex_source"
23
+ },
24
+ "status": {
25
+ "copy_drawio": "exists",
26
+ "copy_png": "exists",
27
+ "diagram_pdf": "pdf_exists",
28
+ "intro_method": "exists",
29
+ "paper_pdf": "exists",
30
+ "latex": "exists"
31
+ }
32
+ }
2006.09447/record.json ADDED
@@ -0,0 +1,32 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "arxiv_id": "2006.09447",
3
+ "month": "2020_06",
4
+ "year": 2021,
5
+ "conference": "NEURIPS",
6
+ "title": "Agent Modelling under Partial Observability for Deep Reinforcement Learning",
7
+ "arxiv_url": "https://arxiv.org/abs/2006.09447",
8
+ "source": {
9
+ "paper_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2020_06/main_diagram_database/2006.09447",
10
+ "tex_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2020_06/tex_files_extracted/2006.09447",
11
+ "paper_md": "/home/zling/lzl/ICML2026/Build_Dataset/data/2020_06/main_diagram_database/2006.09447/paper_text/paper.md",
12
+ "metadata_json": "/home/zling/lzl/ICML2026/Build_Dataset/data/2020_06/main_diagram_database/2006.09447/metadata.json",
13
+ "intro_method_from": "/home/zling/lzl/ICML2026/Build_Dataset/data/2020_06/main_diagram_database/2006.09447/paper_text/paper.md",
14
+ "intro_method_from_kind": "markdown"
15
+ },
16
+ "files": {
17
+ "main_drawio": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2006.09447/main_diagram/main_diagram.drawio",
18
+ "main_png": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2006.09447/main_diagram/main_diagram.png",
19
+ "main_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2006.09447/main_diagram/main_diagram.pdf",
20
+ "intro_method_md": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2006.09447/paper_text/intro_method.md",
21
+ "paper_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2006.09447/paper.pdf",
22
+ "latex": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2006.09447/latex_source"
23
+ },
24
+ "status": {
25
+ "copy_drawio": "exists",
26
+ "copy_png": "exists",
27
+ "diagram_pdf": "pdf_exists",
28
+ "intro_method": "exists",
29
+ "paper_pdf": "exists",
30
+ "latex": "exists"
31
+ }
32
+ }
2012.09446/record.json ADDED
@@ -0,0 +1,32 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "arxiv_id": "2012.09446",
3
+ "month": "2020_12",
4
+ "year": 2021,
5
+ "conference": "AAAI",
6
+ "title": "Unsupervised Learning of Discourse Structures using a Tree Autoencoder",
7
+ "arxiv_url": "https://arxiv.org/abs/2012.09446",
8
+ "source": {
9
+ "paper_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2020_12/main_diagram_database/2012.09446",
10
+ "tex_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2020_12/tex_files_extracted/2012.09446",
11
+ "paper_md": "/home/zling/lzl/ICML2026/Build_Dataset/data/2020_12/main_diagram_database/2012.09446/paper_text/paper.md",
12
+ "metadata_json": "/home/zling/lzl/ICML2026/Build_Dataset/data/2020_12/main_diagram_database/2012.09446/metadata.json",
13
+ "intro_method_from": "/home/zling/lzl/ICML2026/Build_Dataset/data/2020_12/main_diagram_database/2012.09446/paper_text/paper.md",
14
+ "intro_method_from_kind": "markdown"
15
+ },
16
+ "files": {
17
+ "main_drawio": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2012.09446/main_diagram/main_diagram.drawio",
18
+ "main_png": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2012.09446/main_diagram/main_diagram.png",
19
+ "main_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2012.09446/main_diagram/main_diagram.pdf",
20
+ "intro_method_md": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2012.09446/paper_text/intro_method.md",
21
+ "paper_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2012.09446/paper.pdf",
22
+ "latex": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2012.09446/latex_source"
23
+ },
24
+ "status": {
25
+ "copy_drawio": "exists",
26
+ "copy_png": "exists",
27
+ "diagram_pdf": "pdf_exists",
28
+ "intro_method": "exists",
29
+ "paper_pdf": "exists",
30
+ "latex": "exists"
31
+ }
32
+ }
2101.06969/record.json ADDED
@@ -0,0 +1,32 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "arxiv_id": "2101.06969",
3
+ "month": "2021_01",
4
+ "year": 2022,
5
+ "conference": "ICLR",
6
+ "title": "Red Alarm for Pre-trained Models: Universal Vulnerability to Neuron-Level Backdoor Attacks",
7
+ "arxiv_url": "https://arxiv.org/abs/2101.06969",
8
+ "source": {
9
+ "paper_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_01/main_diagram_database/2101.06969",
10
+ "tex_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_01/tex_files_extracted/2101.06969",
11
+ "paper_md": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_01/main_diagram_database/2101.06969/paper_text/paper.md",
12
+ "metadata_json": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_01/main_diagram_database/2101.06969/metadata.json",
13
+ "intro_method_from": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_01/main_diagram_database/2101.06969/paper_text/paper.md",
14
+ "intro_method_from_kind": "markdown"
15
+ },
16
+ "files": {
17
+ "main_drawio": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2101.06969/main_diagram/main_diagram.drawio",
18
+ "main_png": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2101.06969/main_diagram/main_diagram.png",
19
+ "main_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2101.06969/main_diagram/main_diagram.pdf",
20
+ "intro_method_md": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2101.06969/paper_text/intro_method.md",
21
+ "paper_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2101.06969/paper.pdf",
22
+ "latex": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2101.06969/latex_source"
23
+ },
24
+ "status": {
25
+ "copy_drawio": "exists",
26
+ "copy_png": "exists",
27
+ "diagram_pdf": "pdf_exists",
28
+ "intro_method": "exists",
29
+ "paper_pdf": "exists",
30
+ "latex": "exists"
31
+ }
32
+ }
2101.08165/record.json ADDED
@@ -0,0 +1,32 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "arxiv_id": "2101.08165",
3
+ "month": "2021_01",
4
+ "year": 2020,
5
+ "conference": "ACMMM",
6
+ "title": "Video Relation Detection with Trajectory-aware Multi-modal Features",
7
+ "arxiv_url": "https://arxiv.org/abs/2101.08165",
8
+ "source": {
9
+ "paper_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_01/main_diagram_database/2101.08165",
10
+ "tex_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_01/tex_files_extracted/2101.08165",
11
+ "paper_md": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_01/main_diagram_database/2101.08165/paper_text/paper.md",
12
+ "metadata_json": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_01/main_diagram_database/2101.08165/metadata.json",
13
+ "intro_method_from": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_01/main_diagram_database/2101.08165/paper_text/paper.md",
14
+ "intro_method_from_kind": "markdown"
15
+ },
16
+ "files": {
17
+ "main_drawio": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2101.08165/main_diagram/main_diagram.drawio",
18
+ "main_png": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2101.08165/main_diagram/main_diagram.png",
19
+ "main_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2101.08165/main_diagram/main_diagram.pdf",
20
+ "intro_method_md": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2101.08165/paper_text/intro_method.md",
21
+ "paper_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2101.08165/paper.pdf",
22
+ "latex": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2101.08165/latex_source"
23
+ },
24
+ "status": {
25
+ "copy_drawio": "exists",
26
+ "copy_png": "exists",
27
+ "diagram_pdf": "pdf_exists",
28
+ "intro_method": "exists",
29
+ "paper_pdf": "exists",
30
+ "latex": "exists"
31
+ }
32
+ }
2103.17242/record.json ADDED
@@ -0,0 +1,32 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "arxiv_id": "2103.17242",
3
+ "month": "2021_03",
4
+ "year": 2021,
5
+ "conference": "CVPR",
6
+ "title": "Dogfight: Detecting Drones From Drones Videos",
7
+ "arxiv_url": "https://arxiv.org/abs/2103.17242",
8
+ "source": {
9
+ "paper_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_03/main_diagram_database/2103.17242",
10
+ "tex_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_03/tex_files_extracted/2103.17242",
11
+ "paper_md": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_03/main_diagram_database/2103.17242/paper_text/paper.md",
12
+ "metadata_json": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_03/main_diagram_database/2103.17242/metadata.json",
13
+ "intro_method_from": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_03/main_diagram_database/2103.17242/paper_text/paper.md",
14
+ "intro_method_from_kind": "markdown"
15
+ },
16
+ "files": {
17
+ "main_drawio": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2103.17242/main_diagram/main_diagram.drawio",
18
+ "main_png": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2103.17242/main_diagram/main_diagram.png",
19
+ "main_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2103.17242/main_diagram/main_diagram.pdf",
20
+ "intro_method_md": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2103.17242/paper_text/intro_method.md",
21
+ "paper_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2103.17242/paper.pdf",
22
+ "latex": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2103.17242/latex_source"
23
+ },
24
+ "status": {
25
+ "copy_drawio": "exists",
26
+ "copy_png": "exists",
27
+ "diagram_pdf": "pdf_exists",
28
+ "intro_method": "exists",
29
+ "paper_pdf": "exists",
30
+ "latex": "exists"
31
+ }
32
+ }
2104.08253/record.json ADDED
@@ -0,0 +1,32 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "arxiv_id": "2104.08253",
3
+ "month": "2021_04",
4
+ "year": 2021,
5
+ "conference": "EMNLP",
6
+ "title": "Condenser: a Pre-training Architecture for Dense Retrieval",
7
+ "arxiv_url": "https://arxiv.org/abs/2104.08253",
8
+ "source": {
9
+ "paper_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_04/main_diagram_database/2104.08253",
10
+ "tex_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_04/tex_files_extracted/2104.08253",
11
+ "paper_md": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_04/main_diagram_database/2104.08253/paper_text/paper.md",
12
+ "metadata_json": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_04/main_diagram_database/2104.08253/metadata.json",
13
+ "intro_method_from": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_04/main_diagram_database/2104.08253/paper_text/paper.md",
14
+ "intro_method_from_kind": "markdown"
15
+ },
16
+ "files": {
17
+ "main_drawio": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2104.08253/main_diagram/main_diagram.drawio",
18
+ "main_png": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2104.08253/main_diagram/main_diagram.png",
19
+ "main_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2104.08253/main_diagram/main_diagram.pdf",
20
+ "intro_method_md": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2104.08253/paper_text/intro_method.md",
21
+ "paper_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2104.08253/paper.pdf",
22
+ "latex": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2104.08253/latex_source"
23
+ },
24
+ "status": {
25
+ "copy_drawio": "exists",
26
+ "copy_png": "exists",
27
+ "diagram_pdf": "pdf_exists",
28
+ "intro_method": "exists",
29
+ "paper_pdf": "exists",
30
+ "latex": "exists"
31
+ }
32
+ }
2104.12437/record.json ADDED
@@ -0,0 +1,32 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "arxiv_id": "2104.12437",
3
+ "month": "2021_04",
4
+ "year": 2021,
5
+ "conference": "ICML",
6
+ "title": "Towards Rigorous Interpretations: a Formalisation of Feature Attribution",
7
+ "arxiv_url": "https://arxiv.org/abs/2104.12437",
8
+ "source": {
9
+ "paper_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_04/main_diagram_database/2104.12437",
10
+ "tex_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_04/tex_files_extracted/2104.12437",
11
+ "paper_md": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_04/main_diagram_database/2104.12437/paper_text/paper.md",
12
+ "metadata_json": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_04/main_diagram_database/2104.12437/metadata.json",
13
+ "intro_method_from": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_04/main_diagram_database/2104.12437/paper_text/paper.md",
14
+ "intro_method_from_kind": "markdown"
15
+ },
16
+ "files": {
17
+ "main_drawio": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2104.12437/main_diagram/main_diagram.drawio",
18
+ "main_png": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2104.12437/main_diagram/main_diagram.png",
19
+ "main_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2104.12437/main_diagram/main_diagram.pdf",
20
+ "intro_method_md": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2104.12437/paper_text/intro_method.md",
21
+ "paper_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2104.12437/paper.pdf",
22
+ "latex": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2104.12437/latex_source"
23
+ },
24
+ "status": {
25
+ "copy_drawio": "exists",
26
+ "copy_png": "exists",
27
+ "diagram_pdf": "pdf_exists",
28
+ "intro_method": "exists",
29
+ "paper_pdf": "exists",
30
+ "latex": "exists"
31
+ }
32
+ }
2106.00524/record.json ADDED
@@ -0,0 +1,32 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "arxiv_id": "2106.00524",
3
+ "month": "2021_06",
4
+ "year": 2025,
5
+ "conference": "ICML",
6
+ "title": "EduLLM: Leveraging Large Language Models and Framelet-Based Signed Hypergraph Neural Networks for Student Performance Prediction",
7
+ "arxiv_url": "https://arxiv.org/abs/2106.00524",
8
+ "source": {
9
+ "paper_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_06/main_diagram_database/2106.00524",
10
+ "tex_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_06/tex_files_extracted/2106.00524",
11
+ "paper_md": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_06/main_diagram_database/2106.00524/paper_text/paper.md",
12
+ "metadata_json": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_06/main_diagram_database/2106.00524/metadata.json",
13
+ "intro_method_from": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_06/main_diagram_database/2106.00524/paper_text/paper.md",
14
+ "intro_method_from_kind": "markdown"
15
+ },
16
+ "files": {
17
+ "main_drawio": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2106.00524/main_diagram/main_diagram.drawio",
18
+ "main_png": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2106.00524/main_diagram/main_diagram.png",
19
+ "main_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2106.00524/main_diagram/main_diagram.pdf",
20
+ "intro_method_md": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2106.00524/paper_text/intro_method.md",
21
+ "paper_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2106.00524/paper.pdf",
22
+ "latex": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2106.00524/latex_source"
23
+ },
24
+ "status": {
25
+ "copy_drawio": "exists",
26
+ "copy_png": "exists",
27
+ "diagram_pdf": "pdf_exists",
28
+ "intro_method": "exists",
29
+ "paper_pdf": "exists",
30
+ "latex": "exists"
31
+ }
32
+ }
2106.00985/record.json ADDED
@@ -0,0 +1,32 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "arxiv_id": "2106.00985",
3
+ "month": "2021_06",
4
+ "year": 2021,
5
+ "conference": "ACMMM",
6
+ "title": "Feedback Network for Mutually Boosted Stereo Image Super-Resolution and Disparity Estimation",
7
+ "arxiv_url": "https://arxiv.org/abs/2106.00985",
8
+ "source": {
9
+ "paper_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_06/main_diagram_database/2106.00985",
10
+ "tex_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_06/tex_files_extracted/2106.00985",
11
+ "paper_md": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_06/main_diagram_database/2106.00985/paper_text/paper.md",
12
+ "metadata_json": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_06/main_diagram_database/2106.00985/metadata.json",
13
+ "intro_method_from": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_06/main_diagram_database/2106.00985/paper_text/paper.md",
14
+ "intro_method_from_kind": "markdown"
15
+ },
16
+ "files": {
17
+ "main_drawio": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2106.00985/main_diagram/main_diagram.drawio",
18
+ "main_png": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2106.00985/main_diagram/main_diagram.png",
19
+ "main_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2106.00985/main_diagram/main_diagram.pdf",
20
+ "intro_method_md": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2106.00985/paper_text/intro_method.md",
21
+ "paper_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2106.00985/paper.pdf",
22
+ "latex": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2106.00985/latex_source"
23
+ },
24
+ "status": {
25
+ "copy_drawio": "exists",
26
+ "copy_png": "exists",
27
+ "diagram_pdf": "pdf_exists",
28
+ "intro_method": "exists",
29
+ "paper_pdf": "exists",
30
+ "latex": "exists"
31
+ }
32
+ }
2106.01532/record.json ADDED
@@ -0,0 +1,32 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "arxiv_id": "2106.01532",
3
+ "month": "2021_06",
4
+ "year": 2021,
5
+ "conference": "IJCAI",
6
+ "title": "Noise Doesn't Lie: Towards Universal Detection of Deep Inpainting",
7
+ "arxiv_url": "https://arxiv.org/abs/2106.01532",
8
+ "source": {
9
+ "paper_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_06/main_diagram_database/2106.01532",
10
+ "tex_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_06/tex_files_extracted/2106.01532",
11
+ "paper_md": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_06/main_diagram_database/2106.01532/paper_text/paper.md",
12
+ "metadata_json": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_06/main_diagram_database/2106.01532/metadata.json",
13
+ "intro_method_from": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_06/main_diagram_database/2106.01532/paper_text/paper.md",
14
+ "intro_method_from_kind": "markdown"
15
+ },
16
+ "files": {
17
+ "main_drawio": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2106.01532/main_diagram/main_diagram.drawio",
18
+ "main_png": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2106.01532/main_diagram/main_diagram.png",
19
+ "main_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2106.01532/main_diagram/main_diagram.pdf",
20
+ "intro_method_md": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2106.01532/paper_text/intro_method.md",
21
+ "paper_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2106.01532/paper.pdf",
22
+ "latex": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2106.01532/latex_source"
23
+ },
24
+ "status": {
25
+ "copy_drawio": "exists",
26
+ "copy_png": "exists",
27
+ "diagram_pdf": "pdf_exists",
28
+ "intro_method": "exists",
29
+ "paper_pdf": "exists",
30
+ "latex": "exists"
31
+ }
32
+ }
2106.05321/record.json ADDED
@@ -0,0 +1,32 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "arxiv_id": "2106.05321",
3
+ "month": "2021_06",
4
+ "year": 2022,
5
+ "conference": "CVPR",
6
+ "title": "Learning To Memorize Feature Hallucination for One-Shot Image Generation",
7
+ "arxiv_url": "https://arxiv.org/abs/2106.05321",
8
+ "source": {
9
+ "paper_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_06/main_diagram_database/2106.05321",
10
+ "tex_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_06/tex_files_extracted/2106.05321",
11
+ "paper_md": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_06/main_diagram_database/2106.05321/paper_text/paper.md",
12
+ "metadata_json": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_06/main_diagram_database/2106.05321/metadata.json",
13
+ "intro_method_from": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_06/main_diagram_database/2106.05321/paper_text/paper.md",
14
+ "intro_method_from_kind": "markdown"
15
+ },
16
+ "files": {
17
+ "main_drawio": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2106.05321/main_diagram/main_diagram.drawio",
18
+ "main_png": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2106.05321/main_diagram/main_diagram.png",
19
+ "main_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2106.05321/main_diagram/main_diagram.pdf",
20
+ "intro_method_md": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2106.05321/paper_text/intro_method.md",
21
+ "paper_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2106.05321/paper.pdf",
22
+ "latex": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2106.05321/latex_source"
23
+ },
24
+ "status": {
25
+ "copy_drawio": "exists",
26
+ "copy_png": "exists",
27
+ "diagram_pdf": "pdf_exists",
28
+ "intro_method": "exists",
29
+ "paper_pdf": "exists",
30
+ "latex": "exists"
31
+ }
32
+ }
2106.05409/record.json ADDED
@@ -0,0 +1,32 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "arxiv_id": "2106.05409",
3
+ "month": "2021_06",
4
+ "year": 2021,
5
+ "conference": "NEURIPS",
6
+ "title": "Zero Time Waste: Recycling Predictions in Early Exit Neural Networks",
7
+ "arxiv_url": "https://arxiv.org/abs/2106.05409",
8
+ "source": {
9
+ "paper_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_06/main_diagram_database/2106.05409",
10
+ "tex_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_06/tex_files_extracted/2106.05409",
11
+ "paper_md": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_06/main_diagram_database/2106.05409/paper_text/paper.md",
12
+ "metadata_json": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_06/main_diagram_database/2106.05409/metadata.json",
13
+ "intro_method_from": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_06/main_diagram_database/2106.05409/paper_text/paper.md",
14
+ "intro_method_from_kind": "markdown"
15
+ },
16
+ "files": {
17
+ "main_drawio": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2106.05409/main_diagram/main_diagram.drawio",
18
+ "main_png": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2106.05409/main_diagram/main_diagram.png",
19
+ "main_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2106.05409/main_diagram/main_diagram.pdf",
20
+ "intro_method_md": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2106.05409/paper_text/intro_method.md",
21
+ "paper_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2106.05409/paper.pdf",
22
+ "latex": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2106.05409/latex_source"
23
+ },
24
+ "status": {
25
+ "copy_drawio": "exists",
26
+ "copy_png": "exists",
27
+ "diagram_pdf": "pdf_exists",
28
+ "intro_method": "exists",
29
+ "paper_pdf": "exists",
30
+ "latex": "exists"
31
+ }
32
+ }
2109.04284/record.json ADDED
@@ -0,0 +1,32 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "arxiv_id": "2109.04284",
3
+ "month": "2021_09",
4
+ "year": 2021,
5
+ "conference": "ACMMM",
6
+ "title": "Towards Robust Cross-domain Image Understanding with Unsupervised Noise Removal",
7
+ "arxiv_url": "https://arxiv.org/abs/2109.04284",
8
+ "source": {
9
+ "paper_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_09/main_diagram_database/2109.04284",
10
+ "tex_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_09/tex_files_extracted/2109.04284",
11
+ "paper_md": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_09/main_diagram_database/2109.04284/paper_text/paper.md",
12
+ "metadata_json": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_09/main_diagram_database/2109.04284/metadata.json",
13
+ "intro_method_from": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_09/main_diagram_database/2109.04284/paper_text/paper.md",
14
+ "intro_method_from_kind": "markdown"
15
+ },
16
+ "files": {
17
+ "main_drawio": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2109.04284/main_diagram/main_diagram.drawio",
18
+ "main_png": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2109.04284/main_diagram/main_diagram.png",
19
+ "main_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2109.04284/main_diagram/main_diagram.pdf",
20
+ "intro_method_md": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2109.04284/paper_text/intro_method.md",
21
+ "paper_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2109.04284/paper.pdf",
22
+ "latex": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2109.04284/latex_source"
23
+ },
24
+ "status": {
25
+ "copy_drawio": "exists",
26
+ "copy_png": "exists",
27
+ "diagram_pdf": "pdf_exists",
28
+ "intro_method": "exists",
29
+ "paper_pdf": "exists",
30
+ "latex": "exists"
31
+ }
32
+ }
2109.08303/record.json ADDED
@@ -0,0 +1,32 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "arxiv_id": "2109.08303",
3
+ "month": "2021_09",
4
+ "year": 2022,
5
+ "conference": "AAAI",
6
+ "title": "Compilation of Aggregates in ASP Systems",
7
+ "arxiv_url": "https://arxiv.org/abs/2109.08303",
8
+ "source": {
9
+ "paper_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_09/main_diagram_database/2109.08303",
10
+ "tex_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_09/tex_files_extracted/2109.08303",
11
+ "paper_md": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_09/main_diagram_database/2109.08303/paper_text/paper.md",
12
+ "metadata_json": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_09/main_diagram_database/2109.08303/metadata.json",
13
+ "intro_method_from": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_09/main_diagram_database/2109.08303/paper_text/paper.md",
14
+ "intro_method_from_kind": "markdown"
15
+ },
16
+ "files": {
17
+ "main_drawio": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2109.08303/main_diagram/main_diagram.drawio",
18
+ "main_png": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2109.08303/main_diagram/main_diagram.png",
19
+ "main_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2109.08303/main_diagram/main_diagram.pdf",
20
+ "intro_method_md": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2109.08303/paper_text/intro_method.md",
21
+ "paper_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2109.08303/paper.pdf",
22
+ "latex": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2109.08303/latex_source"
23
+ },
24
+ "status": {
25
+ "copy_drawio": "exists",
26
+ "copy_png": "exists",
27
+ "diagram_pdf": "pdf_exists",
28
+ "intro_method": "exists",
29
+ "paper_pdf": "exists",
30
+ "latex": "exists"
31
+ }
32
+ }
2110.03868/record.json ADDED
@@ -0,0 +1,32 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "arxiv_id": "2110.03868",
3
+ "month": "2021_10",
4
+ "year": 2022,
5
+ "conference": "ACL",
6
+ "title": "Towards Learning (Dis)-Similarity of Source Code from Program Contrasts",
7
+ "arxiv_url": "https://arxiv.org/abs/2110.03868",
8
+ "source": {
9
+ "paper_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_10/main_diagram_database/2110.03868",
10
+ "tex_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_10/tex_files_extracted/2110.03868",
11
+ "paper_md": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_10/main_diagram_database/2110.03868/paper_text/paper.md",
12
+ "metadata_json": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_10/main_diagram_database/2110.03868/metadata.json",
13
+ "intro_method_from": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_10/main_diagram_database/2110.03868/paper_text/paper.md",
14
+ "intro_method_from_kind": "markdown"
15
+ },
16
+ "files": {
17
+ "main_drawio": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2110.03868/main_diagram/main_diagram.drawio",
18
+ "main_png": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2110.03868/main_diagram/main_diagram.png",
19
+ "main_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2110.03868/main_diagram/main_diagram.pdf",
20
+ "intro_method_md": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2110.03868/paper_text/intro_method.md",
21
+ "paper_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2110.03868/paper.pdf",
22
+ "latex": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2110.03868/latex_source"
23
+ },
24
+ "status": {
25
+ "copy_drawio": "exists",
26
+ "copy_png": "exists",
27
+ "diagram_pdf": "pdf_exists",
28
+ "intro_method": "exists",
29
+ "paper_pdf": "exists",
30
+ "latex": "exists"
31
+ }
32
+ }
2111.02827/record.json ADDED
@@ -0,0 +1,32 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "arxiv_id": "2111.02827",
3
+ "month": "2021_11",
4
+ "year": 2022,
5
+ "conference": "ICLR",
6
+ "title": "Towards Learning to Speak and Hear Through Multi-Agent Communication over a Continuous Acoustic Channel",
7
+ "arxiv_url": "https://arxiv.org/abs/2111.02827",
8
+ "source": {
9
+ "paper_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_11/main_diagram_database/2111.02827",
10
+ "tex_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_11/tex_files_extracted/2111.02827",
11
+ "paper_md": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_11/main_diagram_database/2111.02827/paper_text/paper.md",
12
+ "metadata_json": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_11/main_diagram_database/2111.02827/metadata.json",
13
+ "intro_method_from": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_11/main_diagram_database/2111.02827/paper_text/paper.md",
14
+ "intro_method_from_kind": "markdown"
15
+ },
16
+ "files": {
17
+ "main_drawio": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2111.02827/main_diagram/main_diagram.drawio",
18
+ "main_png": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2111.02827/main_diagram/main_diagram.png",
19
+ "main_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2111.02827/main_diagram/main_diagram.pdf",
20
+ "intro_method_md": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2111.02827/paper_text/intro_method.md",
21
+ "paper_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2111.02827/paper.pdf",
22
+ "latex": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2111.02827/latex_source"
23
+ },
24
+ "status": {
25
+ "copy_drawio": "exists",
26
+ "copy_png": "exists",
27
+ "diagram_pdf": "pdf_exists",
28
+ "intro_method": "exists",
29
+ "paper_pdf": "exists",
30
+ "latex": "exists"
31
+ }
32
+ }
2111.10361/record.json ADDED
@@ -0,0 +1,32 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "arxiv_id": "2111.10361",
3
+ "month": "2021_11",
4
+ "year": 2022,
5
+ "conference": "AAAI",
6
+ "title": "Solving Visual Analogies Using Neural Algorithmic Reasoning (Student Abstract)",
7
+ "arxiv_url": "https://arxiv.org/abs/2111.10361",
8
+ "source": {
9
+ "paper_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_11/main_diagram_database/2111.10361",
10
+ "tex_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_11/tex_files_extracted/2111.10361",
11
+ "paper_md": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_11/main_diagram_database/2111.10361/paper_text/paper.md",
12
+ "metadata_json": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_11/main_diagram_database/2111.10361/metadata.json",
13
+ "intro_method_from": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_11/main_diagram_database/2111.10361/paper_text/paper.md",
14
+ "intro_method_from_kind": "markdown"
15
+ },
16
+ "files": {
17
+ "main_drawio": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2111.10361/main_diagram/main_diagram.drawio",
18
+ "main_png": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2111.10361/main_diagram/main_diagram.png",
19
+ "main_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2111.10361/main_diagram/main_diagram.pdf",
20
+ "intro_method_md": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2111.10361/paper_text/intro_method.md",
21
+ "paper_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2111.10361/paper.pdf",
22
+ "latex": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2111.10361/latex_source"
23
+ },
24
+ "status": {
25
+ "copy_drawio": "exists",
26
+ "copy_png": "exists",
27
+ "diagram_pdf": "pdf_exists",
28
+ "intro_method": "exists",
29
+ "paper_pdf": "exists",
30
+ "latex": "exists"
31
+ }
32
+ }
2112.01832/record.json ADDED
@@ -0,0 +1,32 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "arxiv_id": "2112.01832",
3
+ "month": "2021_12",
4
+ "year": 2022,
5
+ "conference": "ECCV",
6
+ "title": "Lightweight Attentional Feature Fusion: A New Baseline for Text-to-Video Retrieval",
7
+ "arxiv_url": "https://arxiv.org/abs/2112.01832",
8
+ "source": {
9
+ "paper_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_12/main_diagram_database/2112.01832",
10
+ "tex_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_12/tex_files_extracted/2112.01832",
11
+ "paper_md": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_12/main_diagram_database/2112.01832/paper_text/paper.md",
12
+ "metadata_json": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_12/main_diagram_database/2112.01832/metadata.json",
13
+ "intro_method_from": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_12/main_diagram_database/2112.01832/paper_text/paper.md",
14
+ "intro_method_from_kind": "markdown"
15
+ },
16
+ "files": {
17
+ "main_drawio": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2112.01832/main_diagram/main_diagram.drawio",
18
+ "main_png": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2112.01832/main_diagram/main_diagram.png",
19
+ "main_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2112.01832/main_diagram/main_diagram.pdf",
20
+ "intro_method_md": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2112.01832/paper_text/intro_method.md",
21
+ "paper_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2112.01832/paper.pdf",
22
+ "latex": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2112.01832/latex_source"
23
+ },
24
+ "status": {
25
+ "copy_drawio": "exists",
26
+ "copy_png": "exists",
27
+ "diagram_pdf": "pdf_exists",
28
+ "intro_method": "exists",
29
+ "paper_pdf": "exists",
30
+ "latex": "exists"
31
+ }
32
+ }
2201.01928/record.json ADDED
@@ -0,0 +1,32 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "arxiv_id": "2201.01928",
3
+ "month": "2022_01",
4
+ "year": 2022,
5
+ "conference": "CVPR",
6
+ "title": "Egocentric Deep Multi-Channel Audio-Visual Active Speaker Localization",
7
+ "arxiv_url": "https://arxiv.org/abs/2201.01928",
8
+ "source": {
9
+ "paper_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_01/main_diagram_database/2201.01928",
10
+ "tex_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_01/tex_files_extracted/2201.01928",
11
+ "paper_md": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_01/main_diagram_database/2201.01928/paper_text/paper.md",
12
+ "metadata_json": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_01/main_diagram_database/2201.01928/metadata.json",
13
+ "intro_method_from": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_01/main_diagram_database/2201.01928/paper_text/paper.md",
14
+ "intro_method_from_kind": "markdown"
15
+ },
16
+ "files": {
17
+ "main_drawio": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2201.01928/main_diagram/main_diagram.drawio",
18
+ "main_png": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2201.01928/main_diagram/main_diagram.png",
19
+ "main_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2201.01928/main_diagram/main_diagram.pdf",
20
+ "intro_method_md": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2201.01928/paper_text/intro_method.md",
21
+ "paper_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2201.01928/paper.pdf",
22
+ "latex": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2201.01928/latex_source"
23
+ },
24
+ "status": {
25
+ "copy_drawio": "exists",
26
+ "copy_png": "exists",
27
+ "diagram_pdf": "pdf_exists",
28
+ "intro_method": "exists",
29
+ "paper_pdf": "exists",
30
+ "latex": "exists"
31
+ }
32
+ }
2201.06931/record.json ADDED
@@ -0,0 +1,32 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "arxiv_id": "2201.06931",
3
+ "month": "2022_01",
4
+ "year": 2023,
5
+ "conference": "AAAI",
6
+ "title": "Deep Equilibrium Models for Snapshot Compressive Imaging",
7
+ "arxiv_url": "https://arxiv.org/abs/2201.06931",
8
+ "source": {
9
+ "paper_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_01/main_diagram_database/2201.06931",
10
+ "tex_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_01/tex_files_extracted/2201.06931",
11
+ "paper_md": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_01/main_diagram_database/2201.06931/paper_text/paper.md",
12
+ "metadata_json": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_01/main_diagram_database/2201.06931/metadata.json",
13
+ "intro_method_from": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_01/main_diagram_database/2201.06931/paper_text/paper.md",
14
+ "intro_method_from_kind": "markdown"
15
+ },
16
+ "files": {
17
+ "main_drawio": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2201.06931/main_diagram/main_diagram.drawio",
18
+ "main_png": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2201.06931/main_diagram/main_diagram.png",
19
+ "main_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2201.06931/main_diagram/main_diagram.pdf",
20
+ "intro_method_md": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2201.06931/paper_text/intro_method.md",
21
+ "paper_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2201.06931/paper.pdf",
22
+ "latex": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2201.06931/latex_source"
23
+ },
24
+ "status": {
25
+ "copy_drawio": "exists",
26
+ "copy_png": "exists",
27
+ "diagram_pdf": "pdf_exists",
28
+ "intro_method": "exists",
29
+ "paper_pdf": "exists",
30
+ "latex": "exists"
31
+ }
32
+ }
2201.10649/record.json ADDED
@@ -0,0 +1,32 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "arxiv_id": "2201.10649",
3
+ "month": "2022_01",
4
+ "year": 2021,
5
+ "conference": "ICCV",
6
+ "title": "Task Switching Network for Multi-Task Learning",
7
+ "arxiv_url": "https://arxiv.org/abs/2201.10649",
8
+ "source": {
9
+ "paper_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_01/main_diagram_database/2201.10649",
10
+ "tex_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_01/tex_files_extracted/2201.10649",
11
+ "paper_md": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_01/main_diagram_database/2201.10649/paper_text/paper.md",
12
+ "metadata_json": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_01/main_diagram_database/2201.10649/metadata.json",
13
+ "intro_method_from": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_01/main_diagram_database/2201.10649/paper_text/paper.md",
14
+ "intro_method_from_kind": "markdown"
15
+ },
16
+ "files": {
17
+ "main_drawio": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2201.10649/main_diagram/main_diagram.drawio",
18
+ "main_png": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2201.10649/main_diagram/main_diagram.png",
19
+ "main_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2201.10649/main_diagram/main_diagram.pdf",
20
+ "intro_method_md": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2201.10649/paper_text/intro_method.md",
21
+ "paper_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2201.10649/paper.pdf",
22
+ "latex": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2201.10649/latex_source"
23
+ },
24
+ "status": {
25
+ "copy_drawio": "exists",
26
+ "copy_png": "exists",
27
+ "diagram_pdf": "pdf_exists",
28
+ "intro_method": "exists",
29
+ "paper_pdf": "exists",
30
+ "latex": "exists"
31
+ }
32
+ }
2201.12438/record.json ADDED
@@ -0,0 +1,32 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "arxiv_id": "2201.12438",
3
+ "month": "2022_01",
4
+ "year": 2022,
5
+ "conference": "AAAI",
6
+ "title": "Commonsense Knowledge Reasoning and Generation with Pre-trained Language Models: A Survey",
7
+ "arxiv_url": "https://arxiv.org/abs/2201.12438",
8
+ "source": {
9
+ "paper_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_01/main_diagram_database/2201.12438",
10
+ "tex_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_01/tex_files_extracted/2201.12438",
11
+ "paper_md": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_01/main_diagram_database/2201.12438/paper_text/paper.md",
12
+ "metadata_json": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_01/main_diagram_database/2201.12438/metadata.json",
13
+ "intro_method_from": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_01/main_diagram_database/2201.12438/paper_text/paper.md",
14
+ "intro_method_from_kind": "markdown"
15
+ },
16
+ "files": {
17
+ "main_drawio": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2201.12438/main_diagram/main_diagram.drawio",
18
+ "main_png": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2201.12438/main_diagram/main_diagram.png",
19
+ "main_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2201.12438/main_diagram/main_diagram.pdf",
20
+ "intro_method_md": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2201.12438/paper_text/intro_method.md",
21
+ "paper_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2201.12438/paper.pdf",
22
+ "latex": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2201.12438/latex_source"
23
+ },
24
+ "status": {
25
+ "copy_drawio": "exists",
26
+ "copy_png": "exists",
27
+ "diagram_pdf": "pdf_exists",
28
+ "intro_method": "exists",
29
+ "paper_pdf": "exists",
30
+ "latex": "exists"
31
+ }
32
+ }
2202.00063/record.json ADDED
@@ -0,0 +1,32 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "arxiv_id": "2202.00063",
3
+ "month": "2022_02",
4
+ "year": 2022,
5
+ "conference": "ICML",
6
+ "title": "Efficient Reinforcement Learning in Block MDPs: A Model-free Representation Learning approach",
7
+ "arxiv_url": "https://arxiv.org/abs/2202.00063",
8
+ "source": {
9
+ "paper_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_02/main_diagram_database/2202.00063",
10
+ "tex_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_02/tex_files_extracted/2202.00063",
11
+ "paper_md": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_02/main_diagram_database/2202.00063/paper_text/paper.md",
12
+ "metadata_json": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_02/main_diagram_database/2202.00063/metadata.json",
13
+ "intro_method_from": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_02/main_diagram_database/2202.00063/paper_text/paper.md",
14
+ "intro_method_from_kind": "markdown"
15
+ },
16
+ "files": {
17
+ "main_drawio": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2202.00063/main_diagram/main_diagram.drawio",
18
+ "main_png": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2202.00063/main_diagram/main_diagram.png",
19
+ "main_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2202.00063/main_diagram/main_diagram.pdf",
20
+ "intro_method_md": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2202.00063/paper_text/intro_method.md",
21
+ "paper_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2202.00063/paper.pdf",
22
+ "latex": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2202.00063/latex_source"
23
+ },
24
+ "status": {
25
+ "copy_drawio": "exists",
26
+ "copy_png": "exists",
27
+ "diagram_pdf": "pdf_exists",
28
+ "intro_method": "exists",
29
+ "paper_pdf": "exists",
30
+ "latex": "exists"
31
+ }
32
+ }
2202.06053/record.json ADDED
@@ -0,0 +1,32 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "arxiv_id": "2202.06053",
3
+ "month": "2022_02",
4
+ "year": 2024,
5
+ "conference": "EMNLP",
6
+ "title": "A Hassle-free Algorithm for Strong Differential Privacy in Federated Learning Systems",
7
+ "arxiv_url": "https://arxiv.org/abs/2202.06053",
8
+ "source": {
9
+ "paper_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_02/main_diagram_database/2202.06053",
10
+ "tex_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_02/tex_files_extracted/2202.06053",
11
+ "paper_md": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_02/main_diagram_database/2202.06053/paper_text/paper.md",
12
+ "metadata_json": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_02/main_diagram_database/2202.06053/metadata.json",
13
+ "intro_method_from": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_02/main_diagram_database/2202.06053/paper_text/paper.md",
14
+ "intro_method_from_kind": "markdown"
15
+ },
16
+ "files": {
17
+ "main_drawio": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2202.06053/main_diagram/main_diagram.drawio",
18
+ "main_png": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2202.06053/main_diagram/main_diagram.png",
19
+ "main_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2202.06053/main_diagram/main_diagram.pdf",
20
+ "intro_method_md": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2202.06053/paper_text/intro_method.md",
21
+ "paper_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2202.06053/paper.pdf",
22
+ "latex": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2202.06053/latex_source"
23
+ },
24
+ "status": {
25
+ "copy_drawio": "exists",
26
+ "copy_png": "exists",
27
+ "diagram_pdf": "pdf_exists",
28
+ "intro_method": "exists",
29
+ "paper_pdf": "exists",
30
+ "latex": "exists"
31
+ }
32
+ }
2203.07259/record.json ADDED
@@ -0,0 +1,32 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "arxiv_id": "2203.07259",
3
+ "month": "2022_03",
4
+ "year": 2022,
5
+ "conference": "EMNLP",
6
+ "title": "The Optimal BERT Surgeon: Scalable and Accurate Second-Order Pruning for Large Language Models",
7
+ "arxiv_url": "https://arxiv.org/abs/2203.07259",
8
+ "source": {
9
+ "paper_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_03/main_diagram_database/2203.07259",
10
+ "tex_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_03/tex_files_extracted/2203.07259",
11
+ "paper_md": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_03/main_diagram_database/2203.07259/paper_text/paper.md",
12
+ "metadata_json": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_03/main_diagram_database/2203.07259/metadata.json",
13
+ "intro_method_from": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_03/main_diagram_database/2203.07259/paper_text/paper.md",
14
+ "intro_method_from_kind": "markdown"
15
+ },
16
+ "files": {
17
+ "main_drawio": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2203.07259/main_diagram/main_diagram.drawio",
18
+ "main_png": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2203.07259/main_diagram/main_diagram.png",
19
+ "main_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2203.07259/main_diagram/main_diagram.pdf",
20
+ "intro_method_md": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2203.07259/paper_text/intro_method.md",
21
+ "paper_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2203.07259/paper.pdf",
22
+ "latex": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2203.07259/latex_source"
23
+ },
24
+ "status": {
25
+ "copy_drawio": "exists",
26
+ "copy_png": "exists",
27
+ "diagram_pdf": "pdf_exists",
28
+ "intro_method": "exists",
29
+ "paper_pdf": "exists",
30
+ "latex": "exists"
31
+ }
32
+ }
2203.10344/record.json ADDED
@@ -0,0 +1,32 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "arxiv_id": "2203.10344",
3
+ "month": "2022_03",
4
+ "year": 2022,
5
+ "conference": "ICLR",
6
+ "title": "No Shifted Augmentations (NSA): strong baselines for self-supervised Anomaly Detection",
7
+ "arxiv_url": "https://arxiv.org/abs/2203.10344",
8
+ "source": {
9
+ "paper_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_03/main_diagram_database/2203.10344",
10
+ "tex_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_03/tex_files_extracted/2203.10344",
11
+ "paper_md": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_03/main_diagram_database/2203.10344/paper_text/paper.md",
12
+ "metadata_json": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_03/main_diagram_database/2203.10344/metadata.json",
13
+ "intro_method_from": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_03/main_diagram_database/2203.10344/paper_text/paper.md",
14
+ "intro_method_from_kind": "markdown"
15
+ },
16
+ "files": {
17
+ "main_drawio": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2203.10344/main_diagram/main_diagram.drawio",
18
+ "main_png": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2203.10344/main_diagram/main_diagram.png",
19
+ "main_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2203.10344/main_diagram/main_diagram.pdf",
20
+ "intro_method_md": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2203.10344/paper_text/intro_method.md",
21
+ "paper_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2203.10344/paper.pdf",
22
+ "latex": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2203.10344/latex_source"
23
+ },
24
+ "status": {
25
+ "copy_drawio": "exists",
26
+ "copy_png": "exists",
27
+ "diagram_pdf": "pdf_exists",
28
+ "intro_method": "exists",
29
+ "paper_pdf": "exists",
30
+ "latex": "exists"
31
+ }
32
+ }
2203.10428/record.json ADDED
@@ -0,0 +1,32 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "arxiv_id": "2203.10428",
3
+ "month": "2022_03",
4
+ "year": 2022,
5
+ "conference": "ICLR",
6
+ "title": "PipeGCN: Efficient Full-Graph Training of Graph Convolutional Networks with Pipelined Feature Communication",
7
+ "arxiv_url": "https://arxiv.org/abs/2203.10428",
8
+ "source": {
9
+ "paper_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_03/main_diagram_database/2203.10428",
10
+ "tex_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_03/tex_files_extracted/2203.10428",
11
+ "paper_md": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_03/main_diagram_database/2203.10428/paper_text/paper.md",
12
+ "metadata_json": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_03/main_diagram_database/2203.10428/metadata.json",
13
+ "intro_method_from": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_03/main_diagram_database/2203.10428/paper_text/paper.md",
14
+ "intro_method_from_kind": "markdown"
15
+ },
16
+ "files": {
17
+ "main_drawio": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2203.10428/main_diagram/main_diagram.drawio",
18
+ "main_png": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2203.10428/main_diagram/main_diagram.png",
19
+ "main_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2203.10428/main_diagram/main_diagram.pdf",
20
+ "intro_method_md": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2203.10428/paper_text/intro_method.md",
21
+ "paper_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2203.10428/paper.pdf",
22
+ "latex": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2203.10428/latex_source"
23
+ },
24
+ "status": {
25
+ "copy_drawio": "exists",
26
+ "copy_png": "exists",
27
+ "diagram_pdf": "pdf_exists",
28
+ "intro_method": "exists",
29
+ "paper_pdf": "exists",
30
+ "latex": "exists"
31
+ }
32
+ }
2203.12121/record.json ADDED
@@ -0,0 +1,32 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "arxiv_id": "2203.12121",
3
+ "month": "2022_03",
4
+ "year": 2024,
5
+ "conference": "ACMMM",
6
+ "title": "CBNet: Cooperation-Based Weakly Supervised Polyp Detection",
7
+ "arxiv_url": "https://arxiv.org/abs/2203.12121",
8
+ "source": {
9
+ "paper_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_03/main_diagram_database/2203.12121",
10
+ "tex_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_03/tex_files_extracted/2203.12121",
11
+ "paper_md": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_03/main_diagram_database/2203.12121/paper_text/paper.md",
12
+ "metadata_json": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_03/main_diagram_database/2203.12121/metadata.json",
13
+ "intro_method_from": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_03/main_diagram_database/2203.12121/paper_text/paper.md",
14
+ "intro_method_from_kind": "markdown"
15
+ },
16
+ "files": {
17
+ "main_drawio": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2203.12121/main_diagram/main_diagram.drawio",
18
+ "main_png": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2203.12121/main_diagram/main_diagram.png",
19
+ "main_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2203.12121/main_diagram/main_diagram.pdf",
20
+ "intro_method_md": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2203.12121/paper_text/intro_method.md",
21
+ "paper_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2203.12121/paper.pdf",
22
+ "latex": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2203.12121/latex_source"
23
+ },
24
+ "status": {
25
+ "copy_drawio": "exists",
26
+ "copy_png": "exists",
27
+ "diagram_pdf": "pdf_exists",
28
+ "intro_method": "exists",
29
+ "paper_pdf": "exists",
30
+ "latex": "exists"
31
+ }
32
+ }
2204.10358/record.json ADDED
@@ -0,0 +1,32 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "arxiv_id": "2204.10358",
3
+ "month": "2022_04",
4
+ "year": 2023,
5
+ "conference": "IJCAI",
6
+ "title": "Creative Problem Solving in Artificially Intelligent Agents: A Survey and Framework (Extended Abstract)",
7
+ "arxiv_url": "https://arxiv.org/abs/2204.10358",
8
+ "source": {
9
+ "paper_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_04/main_diagram_database/2204.10358",
10
+ "tex_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_04/tex_files_extracted/2204.10358",
11
+ "paper_md": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_04/main_diagram_database/2204.10358/paper_text/paper.md",
12
+ "metadata_json": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_04/main_diagram_database/2204.10358/metadata.json",
13
+ "intro_method_from": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_04/main_diagram_database/2204.10358/paper_text/paper.md",
14
+ "intro_method_from_kind": "markdown"
15
+ },
16
+ "files": {
17
+ "main_drawio": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2204.10358/main_diagram/main_diagram.drawio",
18
+ "main_png": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2204.10358/main_diagram/main_diagram.png",
19
+ "main_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2204.10358/main_diagram/main_diagram.pdf",
20
+ "intro_method_md": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2204.10358/paper_text/intro_method.md",
21
+ "paper_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2204.10358/paper.pdf",
22
+ "latex": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2204.10358/latex_source"
23
+ },
24
+ "status": {
25
+ "copy_drawio": "exists",
26
+ "copy_png": "exists",
27
+ "diagram_pdf": "pdf_exists",
28
+ "intro_method": "exists",
29
+ "paper_pdf": "exists",
30
+ "latex": "exists"
31
+ }
32
+ }
2204.11910/record.json ADDED
@@ -0,0 +1,32 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "arxiv_id": "2204.11910",
3
+ "month": "2022_04",
4
+ "year": 2023,
5
+ "conference": "AAAI",
6
+ "title": "Integrating Reward Maximization and Population Estimation: Sequential Decision-Making for Internal Revenue Service Audit Selection",
7
+ "arxiv_url": "https://arxiv.org/abs/2204.11910",
8
+ "source": {
9
+ "paper_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_04/main_diagram_database/2204.11910",
10
+ "tex_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_04/tex_files_extracted/2204.11910",
11
+ "paper_md": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_04/main_diagram_database/2204.11910/paper_text/paper.md",
12
+ "metadata_json": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_04/main_diagram_database/2204.11910/metadata.json",
13
+ "intro_method_from": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_04/main_diagram_database/2204.11910/paper_text/paper.md",
14
+ "intro_method_from_kind": "markdown"
15
+ },
16
+ "files": {
17
+ "main_drawio": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2204.11910/main_diagram/main_diagram.drawio",
18
+ "main_png": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2204.11910/main_diagram/main_diagram.png",
19
+ "main_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2204.11910/main_diagram/main_diagram.pdf",
20
+ "intro_method_md": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2204.11910/paper_text/intro_method.md",
21
+ "paper_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2204.11910/paper.pdf",
22
+ "latex": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2204.11910/latex_source"
23
+ },
24
+ "status": {
25
+ "copy_drawio": "exists",
26
+ "copy_png": "exists",
27
+ "diagram_pdf": "pdf_exists",
28
+ "intro_method": "exists",
29
+ "paper_pdf": "exists",
30
+ "latex": "exists"
31
+ }
32
+ }
2204.12322/record.json ADDED
@@ -0,0 +1,32 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "arxiv_id": "2204.12322",
3
+ "month": "2022_04",
4
+ "year": 2022,
5
+ "conference": "IJCAI",
6
+ "title": "RAPQ: Rescuing Accuracy for Power-of-Two Low-bit Post-training Quantization",
7
+ "arxiv_url": "https://arxiv.org/abs/2204.12322",
8
+ "source": {
9
+ "paper_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_04/main_diagram_database/2204.12322",
10
+ "tex_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_04/tex_files_extracted/2204.12322",
11
+ "paper_md": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_04/main_diagram_database/2204.12322/paper_text/paper.md",
12
+ "metadata_json": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_04/main_diagram_database/2204.12322/metadata.json",
13
+ "intro_method_from": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_04/main_diagram_database/2204.12322/paper_text/paper.md",
14
+ "intro_method_from_kind": "markdown"
15
+ },
16
+ "files": {
17
+ "main_drawio": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2204.12322/main_diagram/main_diagram.drawio",
18
+ "main_png": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2204.12322/main_diagram/main_diagram.png",
19
+ "main_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2204.12322/main_diagram/main_diagram.pdf",
20
+ "intro_method_md": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2204.12322/paper_text/intro_method.md",
21
+ "paper_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2204.12322/paper.pdf",
22
+ "latex": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2204.12322/latex_source"
23
+ },
24
+ "status": {
25
+ "copy_drawio": "exists",
26
+ "copy_png": "exists",
27
+ "diagram_pdf": "pdf_exists",
28
+ "intro_method": "exists",
29
+ "paper_pdf": "exists",
30
+ "latex": "exists"
31
+ }
32
+ }
2205.02031/record.json ADDED
@@ -0,0 +1,32 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "arxiv_id": "2205.02031",
3
+ "month": "2022_05",
4
+ "year": 2022,
5
+ "conference": "CVPR",
6
+ "title": "Self-Supervised Super-Resolution for Multi-Exposure Push-Frame Satellites",
7
+ "arxiv_url": "https://arxiv.org/abs/2205.02031",
8
+ "source": {
9
+ "paper_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_05/main_diagram_database/2205.02031",
10
+ "tex_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_05/tex_files_extracted/2205.02031",
11
+ "paper_md": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_05/main_diagram_database/2205.02031/paper_text/paper.md",
12
+ "metadata_json": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_05/main_diagram_database/2205.02031/metadata.json",
13
+ "intro_method_from": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_05/main_diagram_database/2205.02031/paper_text/paper.md",
14
+ "intro_method_from_kind": "markdown"
15
+ },
16
+ "files": {
17
+ "main_drawio": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2205.02031/main_diagram/main_diagram.drawio",
18
+ "main_png": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2205.02031/main_diagram/main_diagram.png",
19
+ "main_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2205.02031/main_diagram/main_diagram.pdf",
20
+ "intro_method_md": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2205.02031/paper_text/intro_method.md",
21
+ "paper_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2205.02031/paper.pdf",
22
+ "latex": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2205.02031/latex_source"
23
+ },
24
+ "status": {
25
+ "copy_drawio": "exists",
26
+ "copy_png": "exists",
27
+ "diagram_pdf": "pdf_exists",
28
+ "intro_method": "exists",
29
+ "paper_pdf": "exists",
30
+ "latex": "exists"
31
+ }
32
+ }
2206.00067/record.json ADDED
@@ -0,0 +1,32 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "arxiv_id": "2206.00067",
3
+ "month": "2022_06",
4
+ "year": 2022,
5
+ "conference": "AAAI",
6
+ "title": "A Short-Term Tropical Cyclone Intensity Forecasting Method Based on High-Order Tensor (Student Abstract)",
7
+ "arxiv_url": "https://arxiv.org/abs/2206.00067",
8
+ "source": {
9
+ "paper_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_06/main_diagram_database/2206.00067",
10
+ "tex_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_06/tex_files_extracted/2206.00067",
11
+ "paper_md": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_06/main_diagram_database/2206.00067/paper_text/paper.md",
12
+ "metadata_json": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_06/main_diagram_database/2206.00067/metadata.json",
13
+ "intro_method_from": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_06/main_diagram_database/2206.00067/paper_text/paper.md",
14
+ "intro_method_from_kind": "markdown"
15
+ },
16
+ "files": {
17
+ "main_drawio": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2206.00067/main_diagram/main_diagram.drawio",
18
+ "main_png": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2206.00067/main_diagram/main_diagram.png",
19
+ "main_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2206.00067/main_diagram/main_diagram.pdf",
20
+ "intro_method_md": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2206.00067/paper_text/intro_method.md",
21
+ "paper_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2206.00067/paper.pdf",
22
+ "latex": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2206.00067/latex_source"
23
+ },
24
+ "status": {
25
+ "copy_drawio": "exists",
26
+ "copy_png": "exists",
27
+ "diagram_pdf": "pdf_exists",
28
+ "intro_method": "exists",
29
+ "paper_pdf": "exists",
30
+ "latex": "exists"
31
+ }
32
+ }
2206.00477/record.json ADDED
@@ -0,0 +1,32 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "arxiv_id": "2206.00477",
3
+ "month": "2022_06",
4
+ "year": 2022,
5
+ "conference": "IJCAI",
6
+ "title": "Anti-Forgery: Towards a Stealthy and Robust DeepFake Disruption Attack via Adversarial Perceptual-aware Perturbations",
7
+ "arxiv_url": "https://arxiv.org/abs/2206.00477",
8
+ "source": {
9
+ "paper_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_06/main_diagram_database/2206.00477",
10
+ "tex_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_06/tex_files_extracted/2206.00477",
11
+ "paper_md": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_06/main_diagram_database/2206.00477/paper_text/paper.md",
12
+ "metadata_json": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_06/main_diagram_database/2206.00477/metadata.json",
13
+ "intro_method_from": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_06/main_diagram_database/2206.00477/paper_text/paper.md",
14
+ "intro_method_from_kind": "markdown"
15
+ },
16
+ "files": {
17
+ "main_drawio": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2206.00477/main_diagram/main_diagram.drawio",
18
+ "main_png": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2206.00477/main_diagram/main_diagram.png",
19
+ "main_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2206.00477/main_diagram/main_diagram.pdf",
20
+ "intro_method_md": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2206.00477/paper_text/intro_method.md",
21
+ "paper_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2206.00477/paper.pdf",
22
+ "latex": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2206.00477/latex_source"
23
+ },
24
+ "status": {
25
+ "copy_drawio": "exists",
26
+ "copy_png": "exists",
27
+ "diagram_pdf": "pdf_exists",
28
+ "intro_method": "exists",
29
+ "paper_pdf": "exists",
30
+ "latex": "exists"
31
+ }
32
+ }
2206.00843/record.json ADDED
@@ -0,0 +1,32 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "arxiv_id": "2206.00843",
3
+ "month": "2022_06",
4
+ "year": 2022,
5
+ "conference": "ICML",
6
+ "title": "DepthShrinker: A New Compression Paradigm Towards Boosting Real-Hardware Efficiency of Compact Neural Networks",
7
+ "arxiv_url": "https://arxiv.org/abs/2206.00843",
8
+ "source": {
9
+ "paper_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_06/main_diagram_database/2206.00843",
10
+ "tex_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_06/tex_files_extracted/2206.00843",
11
+ "paper_md": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_06/main_diagram_database/2206.00843/paper_text/paper.md",
12
+ "metadata_json": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_06/main_diagram_database/2206.00843/metadata.json",
13
+ "intro_method_from": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_06/main_diagram_database/2206.00843/paper_text/paper.md",
14
+ "intro_method_from_kind": "markdown"
15
+ },
16
+ "files": {
17
+ "main_drawio": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2206.00843/main_diagram/main_diagram.drawio",
18
+ "main_png": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2206.00843/main_diagram/main_diagram.png",
19
+ "main_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2206.00843/main_diagram/main_diagram.pdf",
20
+ "intro_method_md": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2206.00843/paper_text/intro_method.md",
21
+ "paper_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2206.00843/paper.pdf",
22
+ "latex": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2206.00843/latex_source"
23
+ },
24
+ "status": {
25
+ "copy_drawio": "exists",
26
+ "copy_png": "exists",
27
+ "diagram_pdf": "pdf_exists",
28
+ "intro_method": "exists",
29
+ "paper_pdf": "exists",
30
+ "latex": "exists"
31
+ }
32
+ }
2206.03674/record.json ADDED
@@ -0,0 +1,32 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "arxiv_id": "2206.03674",
3
+ "month": "2022_06",
4
+ "year": 2023,
5
+ "conference": "ICLR",
6
+ "title": "Integrating Symmetry into Differentiable Planning with Steerable Convolutions",
7
+ "arxiv_url": "https://arxiv.org/abs/2206.03674",
8
+ "source": {
9
+ "paper_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_06/main_diagram_database/2206.03674",
10
+ "tex_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_06/tex_files_extracted/2206.03674",
11
+ "paper_md": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_06/main_diagram_database/2206.03674/paper_text/paper.md",
12
+ "metadata_json": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_06/main_diagram_database/2206.03674/metadata.json",
13
+ "intro_method_from": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_06/main_diagram_database/2206.03674/paper_text/paper.md",
14
+ "intro_method_from_kind": "markdown"
15
+ },
16
+ "files": {
17
+ "main_drawio": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2206.03674/main_diagram/main_diagram.drawio",
18
+ "main_png": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2206.03674/main_diagram/main_diagram.png",
19
+ "main_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2206.03674/main_diagram/main_diagram.pdf",
20
+ "intro_method_md": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2206.03674/paper_text/intro_method.md",
21
+ "paper_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2206.03674/paper.pdf",
22
+ "latex": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2206.03674/latex_source"
23
+ },
24
+ "status": {
25
+ "copy_drawio": "exists",
26
+ "copy_png": "exists",
27
+ "diagram_pdf": "pdf_exists",
28
+ "intro_method": "exists",
29
+ "paper_pdf": "exists",
30
+ "latex": "exists"
31
+ }
32
+ }
2206.08460/record.json ADDED
@@ -0,0 +1,32 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "arxiv_id": "2206.08460",
3
+ "month": "2022_06",
4
+ "year": 2022,
5
+ "conference": "NEURIPS",
6
+ "title": "TUSK: Task-Agnostic Unsupervised Keypoints",
7
+ "arxiv_url": "https://arxiv.org/abs/2206.08460",
8
+ "source": {
9
+ "paper_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_06/main_diagram_database/2206.08460",
10
+ "tex_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_06/tex_files_extracted/2206.08460",
11
+ "paper_md": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_06/main_diagram_database/2206.08460/paper_text/paper.md",
12
+ "metadata_json": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_06/main_diagram_database/2206.08460/metadata.json",
13
+ "intro_method_from": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_06/main_diagram_database/2206.08460/paper_text/paper.md",
14
+ "intro_method_from_kind": "markdown"
15
+ },
16
+ "files": {
17
+ "main_drawio": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2206.08460/main_diagram/main_diagram.drawio",
18
+ "main_png": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2206.08460/main_diagram/main_diagram.png",
19
+ "main_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2206.08460/main_diagram/main_diagram.pdf",
20
+ "intro_method_md": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2206.08460/paper_text/intro_method.md",
21
+ "paper_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2206.08460/paper.pdf",
22
+ "latex": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2206.08460/latex_source"
23
+ },
24
+ "status": {
25
+ "copy_drawio": "exists",
26
+ "copy_png": "exists",
27
+ "diagram_pdf": "pdf_exists",
28
+ "intro_method": "exists",
29
+ "paper_pdf": "exists",
30
+ "latex": "exists"
31
+ }
32
+ }
2206.13606/record.json ADDED
@@ -0,0 +1,32 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "arxiv_id": "2206.13606",
3
+ "month": "2022_06",
4
+ "year": 2020,
5
+ "conference": "IJCAI",
6
+ "title": "Fighting Wildfires under Uncertainty - A Sequential Resource Allocation Approach",
7
+ "arxiv_url": "https://arxiv.org/abs/2206.13606",
8
+ "source": {
9
+ "paper_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_06/main_diagram_database/2206.13606",
10
+ "tex_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_06/tex_files_extracted/2206.13606",
11
+ "paper_md": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_06/main_diagram_database/2206.13606/paper_text/paper.md",
12
+ "metadata_json": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_06/main_diagram_database/2206.13606/metadata.json",
13
+ "intro_method_from": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_06/main_diagram_database/2206.13606/paper_text/paper.md",
14
+ "intro_method_from_kind": "markdown"
15
+ },
16
+ "files": {
17
+ "main_drawio": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2206.13606/main_diagram/main_diagram.drawio",
18
+ "main_png": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2206.13606/main_diagram/main_diagram.png",
19
+ "main_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2206.13606/main_diagram/main_diagram.pdf",
20
+ "intro_method_md": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2206.13606/paper_text/intro_method.md",
21
+ "paper_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2206.13606/paper.pdf",
22
+ "latex": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2206.13606/latex_source"
23
+ },
24
+ "status": {
25
+ "copy_drawio": "exists",
26
+ "copy_png": "exists",
27
+ "diagram_pdf": "pdf_exists",
28
+ "intro_method": "exists",
29
+ "paper_pdf": "exists",
30
+ "latex": "exists"
31
+ }
32
+ }
2207.04873/record.json ADDED
@@ -0,0 +1,32 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "arxiv_id": "2207.04873",
3
+ "month": "2022_07",
4
+ "year": 2022,
5
+ "conference": "ECCV",
6
+ "title": "Hierarchical Average Precision Training for Pertinent Image Retrieval",
7
+ "arxiv_url": "https://arxiv.org/abs/2207.04873",
8
+ "source": {
9
+ "paper_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_07/main_diagram_database/2207.04873",
10
+ "tex_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_07/tex_files_extracted/2207.04873",
11
+ "paper_md": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_07/main_diagram_database/2207.04873/paper_text/paper.md",
12
+ "metadata_json": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_07/main_diagram_database/2207.04873/metadata.json",
13
+ "intro_method_from": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_07/main_diagram_database/2207.04873/paper_text/paper.md",
14
+ "intro_method_from_kind": "markdown"
15
+ },
16
+ "files": {
17
+ "main_drawio": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2207.04873/main_diagram/main_diagram.drawio",
18
+ "main_png": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2207.04873/main_diagram/main_diagram.png",
19
+ "main_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2207.04873/main_diagram/main_diagram.pdf",
20
+ "intro_method_md": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2207.04873/paper_text/intro_method.md",
21
+ "paper_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2207.04873/paper.pdf",
22
+ "latex": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2207.04873/latex_source"
23
+ },
24
+ "status": {
25
+ "copy_drawio": "exists",
26
+ "copy_png": "exists",
27
+ "diagram_pdf": "pdf_exists",
28
+ "intro_method": "exists",
29
+ "paper_pdf": "exists",
30
+ "latex": "exists"
31
+ }
32
+ }
2207.06148/record.json ADDED
@@ -0,0 +1,32 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "arxiv_id": "2207.06148",
3
+ "month": "2022_07",
4
+ "year": 2022,
5
+ "conference": "ACMMM",
6
+ "title": "Multiview Contrastive Learning for Completely Blind Video Quality Assessment of User Generated Content",
7
+ "arxiv_url": "https://arxiv.org/abs/2207.06148",
8
+ "source": {
9
+ "paper_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_07/main_diagram_database/2207.06148",
10
+ "tex_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_07/tex_files_extracted/2207.06148",
11
+ "paper_md": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_07/main_diagram_database/2207.06148/paper_text/paper.md",
12
+ "metadata_json": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_07/main_diagram_database/2207.06148/metadata.json",
13
+ "intro_method_from": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_07/main_diagram_database/2207.06148/paper_text/paper.md",
14
+ "intro_method_from_kind": "markdown"
15
+ },
16
+ "files": {
17
+ "main_drawio": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2207.06148/main_diagram/main_diagram.drawio",
18
+ "main_png": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2207.06148/main_diagram/main_diagram.png",
19
+ "main_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2207.06148/main_diagram/main_diagram.pdf",
20
+ "intro_method_md": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2207.06148/paper_text/intro_method.md",
21
+ "paper_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2207.06148/paper.pdf",
22
+ "latex": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2207.06148/latex_source"
23
+ },
24
+ "status": {
25
+ "copy_drawio": "exists",
26
+ "copy_png": "exists",
27
+ "diagram_pdf": "pdf_exists",
28
+ "intro_method": "exists",
29
+ "paper_pdf": "exists",
30
+ "latex": "exists"
31
+ }
32
+ }
2207.08664/record.json ADDED
@@ -0,0 +1,32 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "arxiv_id": "2207.08664",
3
+ "month": "2022_07",
4
+ "year": 2022,
5
+ "conference": "ECCV",
6
+ "title": "Action-Based Contrastive Learning for Trajectory Prediction",
7
+ "arxiv_url": "https://arxiv.org/abs/2207.08664",
8
+ "source": {
9
+ "paper_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_07/main_diagram_database/2207.08664",
10
+ "tex_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_07/tex_files_extracted/2207.08664",
11
+ "paper_md": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_07/main_diagram_database/2207.08664/paper_text/paper.md",
12
+ "metadata_json": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_07/main_diagram_database/2207.08664/metadata.json",
13
+ "intro_method_from": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_07/main_diagram_database/2207.08664/paper_text/paper.md",
14
+ "intro_method_from_kind": "markdown"
15
+ },
16
+ "files": {
17
+ "main_drawio": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2207.08664/main_diagram/main_diagram.drawio",
18
+ "main_png": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2207.08664/main_diagram/main_diagram.png",
19
+ "main_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2207.08664/main_diagram/main_diagram.pdf",
20
+ "intro_method_md": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2207.08664/paper_text/intro_method.md",
21
+ "paper_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2207.08664/paper.pdf",
22
+ "latex": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2207.08664/latex_source"
23
+ },
24
+ "status": {
25
+ "copy_drawio": "exists",
26
+ "copy_png": "exists",
27
+ "diagram_pdf": "pdf_exists",
28
+ "intro_method": "exists",
29
+ "paper_pdf": "exists",
30
+ "latex": "exists"
31
+ }
32
+ }
2207.10141/record.json ADDED
@@ -0,0 +1,32 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "arxiv_id": "2207.10141",
3
+ "month": "2022_07",
4
+ "year": 2022,
5
+ "conference": "ECCV",
6
+ "title": "AudioScopeV2: Audio-Visual Attention Architectures for Calibrated Open-Domain On-Screen Sound Separation",
7
+ "arxiv_url": "https://arxiv.org/abs/2207.10141",
8
+ "source": {
9
+ "paper_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_07/main_diagram_database/2207.10141",
10
+ "tex_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_07/tex_files_extracted/2207.10141",
11
+ "paper_md": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_07/main_diagram_database/2207.10141/paper_text/paper.md",
12
+ "metadata_json": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_07/main_diagram_database/2207.10141/metadata.json",
13
+ "intro_method_from": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_07/main_diagram_database/2207.10141/paper_text/paper.md",
14
+ "intro_method_from_kind": "markdown"
15
+ },
16
+ "files": {
17
+ "main_drawio": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2207.10141/main_diagram/main_diagram.drawio",
18
+ "main_png": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2207.10141/main_diagram/main_diagram.png",
19
+ "main_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2207.10141/main_diagram/main_diagram.pdf",
20
+ "intro_method_md": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2207.10141/paper_text/intro_method.md",
21
+ "paper_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2207.10141/paper.pdf",
22
+ "latex": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2207.10141/latex_source"
23
+ },
24
+ "status": {
25
+ "copy_drawio": "exists",
26
+ "copy_png": "exists",
27
+ "diagram_pdf": "pdf_exists",
28
+ "intro_method": "exists",
29
+ "paper_pdf": "exists",
30
+ "latex": "exists"
31
+ }
32
+ }
2208.12212/record.json ADDED
@@ -0,0 +1,32 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "arxiv_id": "2208.12212",
3
+ "month": "2022_08",
4
+ "year": 2023,
5
+ "conference": "AAAI",
6
+ "title": "Sustaining Fairness via Incremental Learning",
7
+ "arxiv_url": "https://arxiv.org/abs/2208.12212",
8
+ "source": {
9
+ "paper_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_08/main_diagram_database/2208.12212",
10
+ "tex_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_08/tex_files_extracted/2208.12212",
11
+ "paper_md": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_08/main_diagram_database/2208.12212/paper_text/paper.md",
12
+ "metadata_json": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_08/main_diagram_database/2208.12212/metadata.json",
13
+ "intro_method_from": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_08/main_diagram_database/2208.12212/paper_text/paper.md",
14
+ "intro_method_from_kind": "markdown"
15
+ },
16
+ "files": {
17
+ "main_drawio": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2208.12212/main_diagram/main_diagram.drawio",
18
+ "main_png": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2208.12212/main_diagram/main_diagram.png",
19
+ "main_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2208.12212/main_diagram/main_diagram.pdf",
20
+ "intro_method_md": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2208.12212/paper_text/intro_method.md",
21
+ "paper_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2208.12212/paper.pdf",
22
+ "latex": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2208.12212/latex_source"
23
+ },
24
+ "status": {
25
+ "copy_drawio": "exists",
26
+ "copy_png": "exists",
27
+ "diagram_pdf": "pdf_exists",
28
+ "intro_method": "exists",
29
+ "paper_pdf": "exists",
30
+ "latex": "exists"
31
+ }
32
+ }
2209.06970/record.json ADDED
@@ -0,0 +1,32 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "arxiv_id": "2209.06970",
3
+ "month": "2022_09",
4
+ "year": 2022,
5
+ "conference": "NEURIPS",
6
+ "title": "Generative Visual Prompt: Unifying Distributional Control of Pre-Trained Generative Models",
7
+ "arxiv_url": "https://arxiv.org/abs/2209.06970",
8
+ "source": {
9
+ "paper_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_09/main_diagram_database/2209.06970",
10
+ "tex_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_09/tex_files_extracted/2209.06970",
11
+ "paper_md": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_09/main_diagram_database/2209.06970/paper_text/paper.md",
12
+ "metadata_json": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_09/main_diagram_database/2209.06970/metadata.json",
13
+ "intro_method_from": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_09/main_diagram_database/2209.06970/paper_text/paper.md",
14
+ "intro_method_from_kind": "markdown"
15
+ },
16
+ "files": {
17
+ "main_drawio": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2209.06970/main_diagram/main_diagram.drawio",
18
+ "main_png": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2209.06970/main_diagram/main_diagram.png",
19
+ "main_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2209.06970/main_diagram/main_diagram.pdf",
20
+ "intro_method_md": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2209.06970/paper_text/intro_method.md",
21
+ "paper_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2209.06970/paper.pdf",
22
+ "latex": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2209.06970/latex_source"
23
+ },
24
+ "status": {
25
+ "copy_drawio": "exists",
26
+ "copy_png": "exists",
27
+ "diagram_pdf": "pdf_exists",
28
+ "intro_method": "exists",
29
+ "paper_pdf": "exists",
30
+ "latex": "exists"
31
+ }
32
+ }
2211.02127/record.json ADDED
@@ -0,0 +1,32 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "arxiv_id": "2211.02127",
3
+ "month": "2022_11",
4
+ "year": 2023,
5
+ "conference": "ICML",
6
+ "title": "Scalable Multi-Agent Reinforcement Learning through Intelligent Information Aggregation",
7
+ "arxiv_url": "https://arxiv.org/abs/2211.02127",
8
+ "source": {
9
+ "paper_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_11/main_diagram_database/2211.02127",
10
+ "tex_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_11/tex_files_extracted/2211.02127",
11
+ "paper_md": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_11/main_diagram_database/2211.02127/paper_text/paper.md",
12
+ "metadata_json": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_11/main_diagram_database/2211.02127/metadata.json",
13
+ "intro_method_from": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_11/main_diagram_database/2211.02127/paper_text/paper.md",
14
+ "intro_method_from_kind": "markdown"
15
+ },
16
+ "files": {
17
+ "main_drawio": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2211.02127/main_diagram/main_diagram.drawio",
18
+ "main_png": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2211.02127/main_diagram/main_diagram.png",
19
+ "main_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2211.02127/main_diagram/main_diagram.pdf",
20
+ "intro_method_md": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2211.02127/paper_text/intro_method.md",
21
+ "paper_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2211.02127/paper.pdf",
22
+ "latex": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2211.02127/latex_source"
23
+ },
24
+ "status": {
25
+ "copy_drawio": "exists",
26
+ "copy_png": "exists",
27
+ "diagram_pdf": "pdf_exists",
28
+ "intro_method": "exists",
29
+ "paper_pdf": "exists",
30
+ "latex": "exists"
31
+ }
32
+ }