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Browse filesThis view is limited to 50 files because it contains too many changes. See raw diff
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2002.01612/record.json
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2004.09411/record.json
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2005.00316/record.json
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2006.04016/record.json
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{
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| 5 |
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2006.05580/record.json
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2006.09447/record.json
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{
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| 6 |
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|
| 7 |
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|
| 8 |
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|
| 9 |
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|
| 10 |
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|
| 11 |
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|
| 12 |
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|
| 13 |
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|
| 14 |
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|
| 15 |
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|
| 16 |
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| 17 |
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|
| 18 |
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|
| 19 |
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|
| 20 |
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|
| 21 |
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|
| 22 |
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| 23 |
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| 24 |
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|
| 30 |
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|
| 31 |
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|
| 32 |
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|
2012.09446/record.json
ADDED
|
@@ -0,0 +1,32 @@
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|
|
|
|
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|
|
|
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|
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|
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|
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|
|
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|
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|
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|
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|
|
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|
|
|
|
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|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 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 |
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"tex_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2020_12/tex_files_extracted/2012.09446",
|
| 11 |
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"paper_md": "/home/zling/lzl/ICML2026/Build_Dataset/data/2020_12/main_diagram_database/2012.09446/paper_text/paper.md",
|
| 12 |
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"metadata_json": "/home/zling/lzl/ICML2026/Build_Dataset/data/2020_12/main_diagram_database/2012.09446/metadata.json",
|
| 13 |
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|
| 14 |
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|
| 15 |
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| 16 |
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| 17 |
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|
| 18 |
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|
| 19 |
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| 20 |
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| 22 |
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| 23 |
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| 24 |
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| 25 |
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|
| 30 |
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|
| 31 |
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|
| 32 |
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2101.06969/record.json
ADDED
|
@@ -0,0 +1,32 @@
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|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"arxiv_id": "2101.06969",
|
| 3 |
+
"month": "2021_01",
|
| 4 |
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"year": 2022,
|
| 5 |
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"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 |
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"paper_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_01/main_diagram_database/2101.06969",
|
| 10 |
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"tex_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_01/tex_files_extracted/2101.06969",
|
| 11 |
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"paper_md": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_01/main_diagram_database/2101.06969/paper_text/paper.md",
|
| 12 |
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"metadata_json": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_01/main_diagram_database/2101.06969/metadata.json",
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| 13 |
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|
| 14 |
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"intro_method_from_kind": "markdown"
|
| 15 |
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| 16 |
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| 17 |
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| 18 |
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| 22 |
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| 23 |
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| 24 |
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|
| 30 |
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|
| 31 |
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|
| 32 |
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2101.08165/record.json
ADDED
|
@@ -0,0 +1,32 @@
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|
|
|
|
| 1 |
+
{
|
| 2 |
+
"arxiv_id": "2101.08165",
|
| 3 |
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"month": "2021_01",
|
| 4 |
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"year": 2020,
|
| 5 |
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"conference": "ACMMM",
|
| 6 |
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"title": "Video Relation Detection with Trajectory-aware Multi-modal Features",
|
| 7 |
+
"arxiv_url": "https://arxiv.org/abs/2101.08165",
|
| 8 |
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"source": {
|
| 9 |
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"paper_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_01/main_diagram_database/2101.08165",
|
| 10 |
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"tex_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_01/tex_files_extracted/2101.08165",
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| 11 |
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| 12 |
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| 14 |
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|
| 15 |
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| 18 |
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2103.17242/record.json
ADDED
|
@@ -0,0 +1,32 @@
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|
|
|
|
| 1 |
+
{
|
| 2 |
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"arxiv_id": "2103.17242",
|
| 3 |
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"month": "2021_03",
|
| 4 |
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"year": 2021,
|
| 5 |
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|
| 6 |
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"title": "Dogfight: Detecting Drones From Drones Videos",
|
| 7 |
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|
| 8 |
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"source": {
|
| 9 |
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"paper_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_03/main_diagram_database/2103.17242",
|
| 10 |
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"tex_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_03/tex_files_extracted/2103.17242",
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| 11 |
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"paper_md": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_03/main_diagram_database/2103.17242/paper_text/paper.md",
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| 12 |
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| 14 |
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|
| 15 |
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2104.08253/record.json
ADDED
|
@@ -0,0 +1,32 @@
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|
|
|
|
| 1 |
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{
|
| 2 |
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|
| 3 |
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|
| 4 |
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|
| 5 |
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|
| 6 |
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"title": "Condenser: a Pre-training Architecture for Dense Retrieval",
|
| 7 |
+
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|
| 8 |
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| 9 |
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| 10 |
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| 11 |
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| 12 |
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|
| 15 |
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| 30 |
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|
| 32 |
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2104.12437/record.json
ADDED
|
@@ -0,0 +1,32 @@
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|
|
|
| 1 |
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{
|
| 2 |
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|
| 3 |
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|
| 4 |
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|
| 5 |
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|
| 6 |
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|
| 7 |
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|
| 8 |
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| 9 |
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|
| 10 |
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| 11 |
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| 12 |
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| 13 |
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| 14 |
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|
| 15 |
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| 16 |
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| 17 |
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2106.00524/record.json
ADDED
|
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|
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|
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|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
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|
| 3 |
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|
| 4 |
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|
| 5 |
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|
| 6 |
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|
| 7 |
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|
| 8 |
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| 9 |
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| 10 |
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| 11 |
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|
| 12 |
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| 13 |
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| 14 |
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|
| 15 |
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| 16 |
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| 17 |
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| 18 |
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| 19 |
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| 30 |
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| 31 |
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| 32 |
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2106.00985/record.json
ADDED
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|
|
|
|
| 1 |
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{
|
| 2 |
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|
| 3 |
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|
| 4 |
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|
| 5 |
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|
| 6 |
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|
| 7 |
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|
| 8 |
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| 9 |
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| 10 |
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| 11 |
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| 12 |
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| 14 |
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| 15 |
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| 18 |
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| 30 |
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| 31 |
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| 32 |
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2106.01532/record.json
ADDED
|
@@ -0,0 +1,32 @@
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|
|
|
|
|
| 1 |
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{
|
| 2 |
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|
| 3 |
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|
| 4 |
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|
| 5 |
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|
| 6 |
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|
| 7 |
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|
| 8 |
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| 9 |
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| 10 |
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| 12 |
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2106.05321/record.json
ADDED
|
@@ -0,0 +1,32 @@
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|
|
|
|
| 1 |
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{
|
| 2 |
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|
| 3 |
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|
| 4 |
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|
| 5 |
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|
| 6 |
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"title": "Learning To Memorize Feature Hallucination for One-Shot Image Generation",
|
| 7 |
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|
| 8 |
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| 9 |
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| 10 |
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| 11 |
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| 12 |
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|
| 15 |
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2106.05409/record.json
ADDED
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@@ -0,0 +1,32 @@
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|
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|
|
| 1 |
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{
|
| 2 |
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"arxiv_id": "2106.05409",
|
| 3 |
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|
| 4 |
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|
| 5 |
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|
| 6 |
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|
| 7 |
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|
| 8 |
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| 9 |
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| 10 |
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|
| 31 |
+
}
|
| 32 |
+
}
|
2109.04284/record.json
ADDED
|
@@ -0,0 +1,32 @@
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|
|
|
| 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 |
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"metadata_json": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_09/main_diagram_database/2109.04284/metadata.json",
|
| 13 |
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|
| 14 |
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"intro_method_from_kind": "markdown"
|
| 15 |
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|
| 16 |
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"files": {
|
| 17 |
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"main_drawio": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2109.04284/main_diagram/main_diagram.drawio",
|
| 18 |
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|
| 19 |
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| 20 |
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| 21 |
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| 22 |
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|
| 23 |
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| 24 |
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| 25 |
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| 26 |
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| 27 |
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| 28 |
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| 29 |
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|
| 30 |
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|
| 31 |
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|
| 32 |
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|
2109.08303/record.json
ADDED
|
@@ -0,0 +1,32 @@
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|
|
|
|
| 1 |
+
{
|
| 2 |
+
"arxiv_id": "2109.08303",
|
| 3 |
+
"month": "2021_09",
|
| 4 |
+
"year": 2022,
|
| 5 |
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"conference": "AAAI",
|
| 6 |
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"title": "Compilation of Aggregates in ASP Systems",
|
| 7 |
+
"arxiv_url": "https://arxiv.org/abs/2109.08303",
|
| 8 |
+
"source": {
|
| 9 |
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"paper_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_09/main_diagram_database/2109.08303",
|
| 10 |
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"tex_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_09/tex_files_extracted/2109.08303",
|
| 11 |
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"paper_md": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_09/main_diagram_database/2109.08303/paper_text/paper.md",
|
| 12 |
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"metadata_json": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_09/main_diagram_database/2109.08303/metadata.json",
|
| 13 |
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|
| 14 |
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"intro_method_from_kind": "markdown"
|
| 15 |
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|
| 16 |
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|
| 17 |
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"main_drawio": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2109.08303/main_diagram/main_diagram.drawio",
|
| 18 |
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"main_png": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2109.08303/main_diagram/main_diagram.png",
|
| 19 |
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| 20 |
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| 21 |
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| 22 |
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|
| 23 |
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| 24 |
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| 25 |
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| 26 |
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| 29 |
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|
| 30 |
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|
| 31 |
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|
| 32 |
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|
2110.03868/record.json
ADDED
|
@@ -0,0 +1,32 @@
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|
| 1 |
+
{
|
| 2 |
+
"arxiv_id": "2110.03868",
|
| 3 |
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"month": "2021_10",
|
| 4 |
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"year": 2022,
|
| 5 |
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"conference": "ACL",
|
| 6 |
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"title": "Towards Learning (Dis)-Similarity of Source Code from Program Contrasts",
|
| 7 |
+
"arxiv_url": "https://arxiv.org/abs/2110.03868",
|
| 8 |
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"source": {
|
| 9 |
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"paper_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_10/main_diagram_database/2110.03868",
|
| 10 |
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"tex_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_10/tex_files_extracted/2110.03868",
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| 11 |
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"paper_md": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_10/main_diagram_database/2110.03868/paper_text/paper.md",
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| 12 |
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| 13 |
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| 14 |
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|
| 15 |
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| 16 |
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|
| 17 |
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| 18 |
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| 19 |
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| 22 |
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| 23 |
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| 30 |
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| 31 |
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|
| 32 |
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2111.02827/record.json
ADDED
|
@@ -0,0 +1,32 @@
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|
|
|
|
| 1 |
+
{
|
| 2 |
+
"arxiv_id": "2111.02827",
|
| 3 |
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"month": "2021_11",
|
| 4 |
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"year": 2022,
|
| 5 |
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"conference": "ICLR",
|
| 6 |
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"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 |
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"paper_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_11/main_diagram_database/2111.02827",
|
| 10 |
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"tex_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_11/tex_files_extracted/2111.02827",
|
| 11 |
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"paper_md": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_11/main_diagram_database/2111.02827/paper_text/paper.md",
|
| 12 |
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| 13 |
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| 14 |
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|
| 15 |
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|
| 16 |
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| 17 |
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| 18 |
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| 19 |
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| 22 |
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| 23 |
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| 24 |
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| 25 |
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| 30 |
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|
| 31 |
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|
| 32 |
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2111.10361/record.json
ADDED
|
@@ -0,0 +1,32 @@
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|
|
| 1 |
+
{
|
| 2 |
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"arxiv_id": "2111.10361",
|
| 3 |
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"month": "2021_11",
|
| 4 |
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"year": 2022,
|
| 5 |
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|
| 6 |
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"title": "Solving Visual Analogies Using Neural Algorithmic Reasoning (Student Abstract)",
|
| 7 |
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|
| 8 |
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|
| 9 |
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|
| 10 |
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|
| 11 |
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"paper_md": "/home/zling/lzl/ICML2026/Build_Dataset/data/2021_11/main_diagram_database/2111.10361/paper_text/paper.md",
|
| 12 |
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| 13 |
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|
| 14 |
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|
| 15 |
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|
| 16 |
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| 17 |
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| 18 |
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| 19 |
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| 22 |
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|
| 23 |
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| 24 |
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| 30 |
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|
| 31 |
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|
| 32 |
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2112.01832/record.json
ADDED
|
@@ -0,0 +1,32 @@
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|
|
|
|
| 1 |
+
{
|
| 2 |
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"arxiv_id": "2112.01832",
|
| 3 |
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"month": "2021_12",
|
| 4 |
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"year": 2022,
|
| 5 |
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|
| 6 |
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"title": "Lightweight Attentional Feature Fusion: A New Baseline for Text-to-Video Retrieval",
|
| 7 |
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|
| 8 |
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|
| 9 |
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|
| 10 |
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| 11 |
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|
| 12 |
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| 13 |
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|
| 14 |
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|
| 15 |
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| 16 |
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| 17 |
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| 18 |
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| 19 |
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| 21 |
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|
| 22 |
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"latex": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2112.01832/latex_source"
|
| 23 |
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| 24 |
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| 25 |
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|
| 26 |
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| 27 |
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| 28 |
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| 29 |
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|
| 30 |
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|
| 31 |
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|
| 32 |
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|
2201.01928/record.json
ADDED
|
@@ -0,0 +1,32 @@
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|
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|
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|
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|
|
|
|
|
| 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 |
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"metadata_json": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_01/main_diagram_database/2201.01928/metadata.json",
|
| 13 |
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|
| 14 |
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"intro_method_from_kind": "markdown"
|
| 15 |
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},
|
| 16 |
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"files": {
|
| 17 |
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"main_drawio": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2201.01928/main_diagram/main_diagram.drawio",
|
| 18 |
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"main_png": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2201.01928/main_diagram/main_diagram.png",
|
| 19 |
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|
| 20 |
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| 21 |
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| 22 |
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|
| 23 |
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| 24 |
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|
| 25 |
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| 26 |
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| 27 |
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| 28 |
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|
| 29 |
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|
| 30 |
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|
| 31 |
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|
| 32 |
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|
2201.06931/record.json
ADDED
|
@@ -0,0 +1,32 @@
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|
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|
|
|
|
|
|
|
| 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 |
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"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 |
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"paper_md": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_01/main_diagram_database/2201.06931/paper_text/paper.md",
|
| 12 |
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"metadata_json": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_01/main_diagram_database/2201.06931/metadata.json",
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| 13 |
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|
| 14 |
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"intro_method_from_kind": "markdown"
|
| 15 |
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|
| 16 |
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|
| 17 |
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| 18 |
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| 19 |
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| 21 |
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| 22 |
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|
| 23 |
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| 24 |
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| 25 |
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| 26 |
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| 30 |
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| 31 |
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|
| 32 |
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|
2201.10649/record.json
ADDED
|
@@ -0,0 +1,32 @@
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|
|
|
|
| 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 |
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"paper_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_01/main_diagram_database/2201.10649",
|
| 10 |
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"tex_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_01/tex_files_extracted/2201.10649",
|
| 11 |
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"paper_md": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_01/main_diagram_database/2201.10649/paper_text/paper.md",
|
| 12 |
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| 13 |
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|
| 14 |
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|
| 15 |
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| 16 |
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| 17 |
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| 18 |
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| 19 |
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| 30 |
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| 31 |
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| 32 |
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2201.12438/record.json
ADDED
|
@@ -0,0 +1,32 @@
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|
|
|
|
| 1 |
+
{
|
| 2 |
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"arxiv_id": "2201.12438",
|
| 3 |
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"month": "2022_01",
|
| 4 |
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"year": 2022,
|
| 5 |
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|
| 6 |
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"title": "Commonsense Knowledge Reasoning and Generation with Pre-trained Language Models: A Survey",
|
| 7 |
+
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|
| 8 |
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"source": {
|
| 9 |
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"paper_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_01/main_diagram_database/2201.12438",
|
| 10 |
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"tex_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_01/tex_files_extracted/2201.12438",
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| 11 |
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|
| 12 |
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| 13 |
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| 14 |
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|
| 15 |
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| 16 |
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| 17 |
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| 18 |
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| 23 |
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| 30 |
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| 31 |
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2202.00063/record.json
ADDED
|
@@ -0,0 +1,32 @@
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|
|
|
|
| 1 |
+
{
|
| 2 |
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|
| 3 |
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|
| 4 |
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|
| 5 |
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|
| 6 |
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|
| 7 |
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|
| 8 |
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| 9 |
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| 10 |
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| 11 |
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| 12 |
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|
| 15 |
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| 30 |
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| 31 |
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2202.06053/record.json
ADDED
|
@@ -0,0 +1,32 @@
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|
|
|
|
|
|
| 1 |
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{
|
| 2 |
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"arxiv_id": "2202.06053",
|
| 3 |
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|
| 4 |
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|
| 5 |
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|
| 6 |
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|
| 7 |
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|
| 8 |
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| 9 |
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| 10 |
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| 11 |
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| 14 |
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|
| 15 |
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|
| 16 |
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|
| 17 |
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|
| 18 |
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|
| 19 |
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|
| 20 |
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|
| 21 |
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|
| 22 |
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|
| 23 |
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|
| 24 |
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| 25 |
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| 26 |
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|
| 29 |
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|
| 30 |
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|
| 31 |
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|
| 32 |
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|
2203.07259/record.json
ADDED
|
@@ -0,0 +1,32 @@
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|
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|
|
|
|
|
| 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 |
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"paper_md": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_03/main_diagram_database/2203.07259/paper_text/paper.md",
|
| 12 |
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"metadata_json": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_03/main_diagram_database/2203.07259/metadata.json",
|
| 13 |
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|
| 14 |
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"intro_method_from_kind": "markdown"
|
| 15 |
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|
| 16 |
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"files": {
|
| 17 |
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|
| 18 |
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"main_png": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2203.07259/main_diagram/main_diagram.png",
|
| 19 |
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| 20 |
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| 21 |
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| 22 |
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|
| 23 |
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| 24 |
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| 25 |
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| 26 |
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| 29 |
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|
| 30 |
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|
| 31 |
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|
| 32 |
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|
2203.10344/record.json
ADDED
|
@@ -0,0 +1,32 @@
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|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"arxiv_id": "2203.10344",
|
| 3 |
+
"month": "2022_03",
|
| 4 |
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"year": 2022,
|
| 5 |
+
"conference": "ICLR",
|
| 6 |
+
"title": "No Shifted Augmentations (NSA): strong baselines for self-supervised Anomaly Detection",
|
| 7 |
+
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|
| 8 |
+
"source": {
|
| 9 |
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"paper_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_03/main_diagram_database/2203.10344",
|
| 10 |
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"tex_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_03/tex_files_extracted/2203.10344",
|
| 11 |
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"paper_md": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_03/main_diagram_database/2203.10344/paper_text/paper.md",
|
| 12 |
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"metadata_json": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_03/main_diagram_database/2203.10344/metadata.json",
|
| 13 |
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|
| 14 |
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"intro_method_from_kind": "markdown"
|
| 15 |
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| 16 |
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| 17 |
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| 18 |
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| 19 |
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| 22 |
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| 23 |
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| 24 |
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| 26 |
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|
| 30 |
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|
| 31 |
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|
| 32 |
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2203.10428/record.json
ADDED
|
@@ -0,0 +1,32 @@
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|
|
| 1 |
+
{
|
| 2 |
+
"arxiv_id": "2203.10428",
|
| 3 |
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"month": "2022_03",
|
| 4 |
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"year": 2022,
|
| 5 |
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"conference": "ICLR",
|
| 6 |
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"title": "PipeGCN: Efficient Full-Graph Training of Graph Convolutional Networks with Pipelined Feature Communication",
|
| 7 |
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"arxiv_url": "https://arxiv.org/abs/2203.10428",
|
| 8 |
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"source": {
|
| 9 |
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"paper_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_03/main_diagram_database/2203.10428",
|
| 10 |
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"tex_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_03/tex_files_extracted/2203.10428",
|
| 11 |
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| 12 |
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| 13 |
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| 14 |
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|
| 15 |
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| 16 |
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| 18 |
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| 30 |
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| 31 |
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|
| 32 |
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2203.12121/record.json
ADDED
|
@@ -0,0 +1,32 @@
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|
|
| 1 |
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{
|
| 2 |
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|
| 3 |
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|
| 4 |
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|
| 5 |
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|
| 6 |
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"title": "CBNet: Cooperation-Based Weakly Supervised Polyp Detection",
|
| 7 |
+
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|
| 8 |
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"source": {
|
| 9 |
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|
| 10 |
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| 11 |
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| 12 |
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| 14 |
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|
| 15 |
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| 16 |
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| 17 |
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| 18 |
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| 23 |
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| 30 |
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| 31 |
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2204.10358/record.json
ADDED
|
@@ -0,0 +1,32 @@
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|
|
| 1 |
+
{
|
| 2 |
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"arxiv_id": "2204.10358",
|
| 3 |
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|
| 4 |
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|
| 5 |
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|
| 6 |
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|
| 7 |
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|
| 8 |
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|
| 9 |
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|
| 10 |
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| 11 |
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| 12 |
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| 14 |
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|
| 15 |
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| 16 |
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| 17 |
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| 18 |
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| 23 |
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| 30 |
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| 31 |
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|
| 32 |
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2204.11910/record.json
ADDED
|
@@ -0,0 +1,32 @@
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|
|
|
|
| 1 |
+
{
|
| 2 |
+
"arxiv_id": "2204.11910",
|
| 3 |
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"month": "2022_04",
|
| 4 |
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"year": 2023,
|
| 5 |
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"conference": "AAAI",
|
| 6 |
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|
| 7 |
+
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|
| 8 |
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|
| 9 |
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|
| 10 |
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|
| 11 |
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|
| 12 |
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|
| 13 |
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|
| 14 |
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|
| 15 |
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|
| 16 |
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|
| 17 |
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| 18 |
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|
| 19 |
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|
| 20 |
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|
| 21 |
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|
| 22 |
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|
| 23 |
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| 24 |
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| 25 |
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|
| 30 |
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|
| 31 |
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|
| 32 |
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|
2204.12322/record.json
ADDED
|
@@ -0,0 +1,32 @@
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|
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|
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|
|
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|
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|
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|
|
|
|
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|
|
|
|
|
|
|
| 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 |
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"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 |
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"paper_md": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_04/main_diagram_database/2204.12322/paper_text/paper.md",
|
| 12 |
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"metadata_json": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_04/main_diagram_database/2204.12322/metadata.json",
|
| 13 |
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|
| 14 |
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|
| 15 |
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|
| 16 |
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| 17 |
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|
| 18 |
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| 19 |
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| 20 |
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| 22 |
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| 23 |
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| 24 |
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| 25 |
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| 26 |
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| 28 |
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| 29 |
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|
| 30 |
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|
| 31 |
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|
| 32 |
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2205.02031/record.json
ADDED
|
@@ -0,0 +1,32 @@
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|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"arxiv_id": "2205.02031",
|
| 3 |
+
"month": "2022_05",
|
| 4 |
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"year": 2022,
|
| 5 |
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"conference": "CVPR",
|
| 6 |
+
"title": "Self-Supervised Super-Resolution for Multi-Exposure Push-Frame Satellites",
|
| 7 |
+
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|
| 8 |
+
"source": {
|
| 9 |
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"paper_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_05/main_diagram_database/2205.02031",
|
| 10 |
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"tex_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_05/tex_files_extracted/2205.02031",
|
| 11 |
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"paper_md": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_05/main_diagram_database/2205.02031/paper_text/paper.md",
|
| 12 |
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|
| 13 |
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|
| 14 |
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"intro_method_from_kind": "markdown"
|
| 15 |
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| 16 |
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| 17 |
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| 18 |
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| 19 |
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| 22 |
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| 23 |
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| 30 |
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| 31 |
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|
| 32 |
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2206.00067/record.json
ADDED
|
@@ -0,0 +1,32 @@
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|
|
| 1 |
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{
|
| 2 |
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|
| 3 |
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|
| 4 |
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"year": 2022,
|
| 5 |
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|
| 6 |
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"title": "A Short-Term Tropical Cyclone Intensity Forecasting Method Based on High-Order Tensor (Student Abstract)",
|
| 7 |
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|
| 8 |
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| 9 |
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| 10 |
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| 11 |
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| 12 |
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| 14 |
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|
| 15 |
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| 17 |
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| 18 |
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| 30 |
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| 31 |
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| 32 |
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2206.00477/record.json
ADDED
|
@@ -0,0 +1,32 @@
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|
| 1 |
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{
|
| 2 |
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|
| 3 |
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|
| 4 |
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|
| 5 |
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|
| 6 |
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"title": "Anti-Forgery: Towards a Stealthy and Robust DeepFake Disruption Attack via Adversarial Perceptual-aware Perturbations",
|
| 7 |
+
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|
| 8 |
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| 9 |
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|
| 10 |
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| 11 |
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| 12 |
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|
| 15 |
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| 18 |
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| 23 |
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2206.00843/record.json
ADDED
|
@@ -0,0 +1,32 @@
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|
|
| 1 |
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{
|
| 2 |
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|
| 3 |
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|
| 4 |
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|
| 5 |
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|
| 6 |
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|
| 7 |
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|
| 8 |
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| 9 |
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| 10 |
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| 12 |
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|
| 15 |
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| 16 |
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| 30 |
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| 31 |
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2206.03674/record.json
ADDED
|
@@ -0,0 +1,32 @@
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|
|
|
|
| 1 |
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|
| 2 |
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|
| 3 |
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|
| 4 |
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|
| 5 |
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|
| 6 |
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|
| 7 |
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|
| 8 |
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|
| 9 |
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|
| 10 |
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|
| 11 |
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|
| 12 |
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| 13 |
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|
| 14 |
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|
| 15 |
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| 16 |
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| 17 |
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| 18 |
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| 19 |
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| 20 |
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| 22 |
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| 30 |
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| 31 |
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2206.08460/record.json
ADDED
|
@@ -0,0 +1,32 @@
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|
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|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"arxiv_id": "2206.08460",
|
| 3 |
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"month": "2022_06",
|
| 4 |
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|
| 5 |
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|
| 6 |
+
"title": "TUSK: Task-Agnostic Unsupervised Keypoints",
|
| 7 |
+
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|
| 8 |
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|
| 9 |
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"paper_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_06/main_diagram_database/2206.08460",
|
| 10 |
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"tex_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_06/tex_files_extracted/2206.08460",
|
| 11 |
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"paper_md": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_06/main_diagram_database/2206.08460/paper_text/paper.md",
|
| 12 |
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| 13 |
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|
| 14 |
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|
| 15 |
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| 16 |
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| 17 |
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| 18 |
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| 19 |
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| 30 |
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| 31 |
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| 32 |
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2206.13606/record.json
ADDED
|
@@ -0,0 +1,32 @@
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|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
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"arxiv_id": "2206.13606",
|
| 3 |
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"month": "2022_06",
|
| 4 |
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|
| 5 |
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|
| 6 |
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"title": "Fighting Wildfires under Uncertainty - A Sequential Resource Allocation Approach",
|
| 7 |
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|
| 8 |
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|
| 9 |
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"paper_dir": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_06/main_diagram_database/2206.13606",
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| 10 |
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| 11 |
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"paper_md": "/home/zling/lzl/ICML2026/Build_Dataset/data/2022_06/main_diagram_database/2206.13606/paper_text/paper.md",
|
| 12 |
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| 13 |
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| 14 |
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| 15 |
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| 16 |
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| 18 |
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| 23 |
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| 30 |
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| 31 |
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| 32 |
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2207.04873/record.json
ADDED
|
@@ -0,0 +1,32 @@
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|
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|
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|
|
|
|
|
| 1 |
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{
|
| 2 |
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|
| 3 |
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|
| 4 |
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|
| 5 |
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|
| 6 |
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|
| 7 |
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|
| 8 |
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| 9 |
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| 10 |
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| 11 |
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| 12 |
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2207.06148/record.json
ADDED
|
@@ -0,0 +1,32 @@
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|
|
|
|
| 1 |
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{
|
| 2 |
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|
| 3 |
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|
| 4 |
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"year": 2022,
|
| 5 |
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|
| 6 |
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"title": "Multiview Contrastive Learning for Completely Blind Video Quality Assessment of User Generated Content",
|
| 7 |
+
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|
| 8 |
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| 9 |
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| 10 |
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| 11 |
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| 12 |
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| 14 |
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| 15 |
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2207.08664/record.json
ADDED
|
@@ -0,0 +1,32 @@
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|
| 1 |
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| 2 |
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| 3 |
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|
| 4 |
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|
| 5 |
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|
| 6 |
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|
| 7 |
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|
| 8 |
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| 9 |
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| 10 |
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2207.10141/record.json
ADDED
|
@@ -0,0 +1,32 @@
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|
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|
| 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 |
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"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 |
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"main_drawio": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2207.10141/main_diagram/main_diagram.drawio",
|
| 18 |
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"main_png": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2207.10141/main_diagram/main_diagram.png",
|
| 19 |
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"main_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2207.10141/main_diagram/main_diagram.pdf",
|
| 20 |
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"intro_method_md": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2207.10141/paper_text/intro_method.md",
|
| 21 |
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"paper_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2207.10141/paper.pdf",
|
| 22 |
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"latex": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2207.10141/latex_source"
|
| 23 |
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|
| 24 |
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"status": {
|
| 25 |
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"copy_drawio": "exists",
|
| 26 |
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"copy_png": "exists",
|
| 27 |
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"diagram_pdf": "pdf_exists",
|
| 28 |
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"intro_method": "exists",
|
| 29 |
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"paper_pdf": "exists",
|
| 30 |
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"latex": "exists"
|
| 31 |
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}
|
| 32 |
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}
|
2208.12212/record.json
ADDED
|
@@ -0,0 +1,32 @@
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|
|
|
|
|
|
|
|
|
|
|
| 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 |
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"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 |
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"paper_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2208.12212/paper.pdf",
|
| 22 |
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"latex": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2208.12212/latex_source"
|
| 23 |
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},
|
| 24 |
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"status": {
|
| 25 |
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"copy_drawio": "exists",
|
| 26 |
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"copy_png": "exists",
|
| 27 |
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"diagram_pdf": "pdf_exists",
|
| 28 |
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"intro_method": "exists",
|
| 29 |
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"paper_pdf": "exists",
|
| 30 |
+
"latex": "exists"
|
| 31 |
+
}
|
| 32 |
+
}
|
2209.06970/record.json
ADDED
|
@@ -0,0 +1,32 @@
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|
|
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|
|
|
|
| 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 |
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"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 |
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"status": {
|
| 25 |
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"copy_drawio": "exists",
|
| 26 |
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"copy_png": "exists",
|
| 27 |
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"diagram_pdf": "pdf_exists",
|
| 28 |
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"intro_method": "exists",
|
| 29 |
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"paper_pdf": "exists",
|
| 30 |
+
"latex": "exists"
|
| 31 |
+
}
|
| 32 |
+
}
|
2211.02127/record.json
ADDED
|
@@ -0,0 +1,32 @@
|
|
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|
|
|
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|
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|
|
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|
|
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|
|
|
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|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 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 |
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|
| 14 |
+
"intro_method_from_kind": "markdown"
|
| 15 |
+
},
|
| 16 |
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"files": {
|
| 17 |
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"main_drawio": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2211.02127/main_diagram/main_diagram.drawio",
|
| 18 |
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"main_png": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2211.02127/main_diagram/main_diagram.png",
|
| 19 |
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"main_pdf": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2211.02127/main_diagram/main_diagram.pdf",
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| 20 |
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"intro_method_md": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2211.02127/paper_text/intro_method.md",
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| 21 |
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| 22 |
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"latex": "/home/zling/lzl/ICML2026/Build_Dataset/dataset/2211.02127/latex_source"
|
| 23 |
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|
| 24 |
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"status": {
|
| 25 |
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| 26 |
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| 27 |
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| 28 |
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|
| 29 |
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"paper_pdf": "exists",
|
| 30 |
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"latex": "exists"
|
| 31 |
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|
| 32 |
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