barom2 commited on
Commit
12e49bf
ยท
verified ยท
1 Parent(s): 4bebd58

Update README.md

Browse files
Files changed (1) hide show
  1. README.md +176 -45
README.md CHANGED
@@ -38,53 +38,46 @@ Our flagship **Datumo Platform** is Korea's first end-to-end AI trust evaluation
38
 
39
  ## ๐ŸŽฏ What We Do
40
 
41
- <table>
42
- <tr>
43
- <td width="33%" valign="top">
44
-
45
- ### ๐Ÿ—‚๏ธ Data Construction
46
- Training data design &amp; build
47
- Pre-training data licensing
48
- RAG knowledge pipelines
49
- Crowdsourced at scale
50
-
51
- </td>
52
- <td width="33%" valign="top">
53
-
54
- ### ๐Ÿ›ก๏ธ AI Trust &amp; Safety
55
- LLM red-teaming
56
- Reliability benchmarks
57
- Safety evaluation datasets
58
- Guardrail testing
59
-
60
- </td>
61
- <td width="33%" valign="top">
62
-
63
- ### ๐Ÿ“Š Datumo Platform
64
- Automated LLM evaluation
65
- Dashboard analytics
66
- **45 days โ†’ 45 minutes**
67
- End-to-end eval pipeline
68
-
69
- </td>
70
- </tr>
71
- </table>
72
 
73
  ---
74
 
75
  ## ๐Ÿ“š Featured Collections
76
 
77
  ### ๐Ÿ›ก๏ธ [Safety-Data](https://huggingface.co/collections/datumo/safety-data)
 
78
  Curated by our **AI Safety team** โ€” Korean-language safety and reliability benchmarks for LLM evaluation.
79
 
80
- - ๐Ÿ”ธ [**KorSET**](https://huggingface.co/datasets/datumo/KorSET) โ€” Korean Safety Evaluation Toolkit
81
- - ๐Ÿ”ธ [**KorNAT**](https://huggingface.co/datasets/datumo/KorNAT) โ€” Korea's first LLM reliability / national-alignment benchmark
 
 
 
82
 
83
  ### ๐Ÿ“ฆ [Data-Data](https://huggingface.co/collections/datumo/data-data)
84
- Research outputs from our **Data team**.
85
 
86
- - ๐Ÿ”ธ [**CAC-CoT**](https://huggingface.co/datumo/CAC-CoT) โ€” 7B Chain-of-Thought feature extraction model
87
- - ๐Ÿ”ธ [**CAC-CoT dataset**](https://huggingface.co/datasets/datumo/CAC-CoT) โ€” accompanying training data
 
 
 
 
 
 
 
 
 
 
 
88
 
89
  > ๐Ÿ’ก ํŒ”๋กœ์šฐํ•˜์‹œ๋ฉด ์ƒˆ ๋ฐ์ดํ„ฐ์…‹๊ณผ ๋ชจ๋ธ์ด ๊ณต๊ฐœ๋  ๋•Œ ์•Œ๋ฆผ์„ ๋ฐ›์œผ์‹ค ์ˆ˜ ์žˆ์–ด์š”.
90
 
@@ -92,13 +85,150 @@ Research outputs from our **Data team**.
92
 
93
  ## ๐Ÿ† Milestones
94
 
95
- - ๐Ÿ‡ฐ๐Ÿ‡ท **K-AI Company** โ€” Selected for Korea's Sovereign AI Foundation Model Project *(SKT Consortium, data lead)*
96
- - ๐Ÿ… **Forbes Korea "2025 AI 50"**
97
- - ๐Ÿ… **Forbes "30 Under 30 Asia"** โ€” Enterprise Technology
98
- - ๐Ÿš€ **Datumo Eval** โ€” Korea's first automated LLM reliability evaluation platform (2025)
99
- - ๐Ÿ“ˆ **200M+ annotations** ยท **287+ enterprise clients** ยท **250K+ crowdworkers**
100
- - ๐Ÿ“ Co-built landmark Korean benchmarks including **KLUE** and **KorQuAD 2.0**
101
- - ๐Ÿ”ฌ Publications at **NeurIPS ยท EMNLP ยท CVPR**
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
102
 
103
  ---
104
 
@@ -109,10 +239,11 @@ Research outputs from our **Data team**.
109
  | ๐ŸŒ Website | [selectstar.ai](https://selectstar.ai/) |
110
  | ๐Ÿ“ฐ Blog | [selectstar.ai/blog](https://selectstar.ai/blog/) |
111
  | ๐Ÿ’ผ Enterprise inquiries | [Contact form](https://selectstar.ai/contact_page/) |
112
- | ๐Ÿ’ฌ Community | Join the [discussion tab](https://huggingface.co/spaces/datumo/README/discussions) |
 
113
 
114
  ---
115
 
116
  <div align="center">
117
- <sub>โญ Building the data foundation for trustworthy AI &middot; Made with care in Seoul ๐Ÿ‡ฐ๐Ÿ‡ท</sub>
118
  </div>
 
38
 
39
  ## ๐ŸŽฏ What We Do
40
 
41
+ Perception AI(2018~) โ†’ Generative AI(2022~) โ†’ **Agentic AI(2026~)** ๋กœ ์ด์–ด์ง€๋Š” AI ์ง„ํ™” ์ „ ๋‹จ๊ณ„์— ๊ฑธ์ณ, ๋ฐ์ดํ„ฐ ๊ตฌ์ถ•๋ถ€ํ„ฐ ์‹ ๋ขฐ์„ฑ ๊ฒ€์ฆ๊นŒ์ง€ **End-to-End ํŒŒ์ดํ”„๋ผ์ธ**์„ ์ œ๊ณตํ•ฉ๋‹ˆ๋‹ค.
42
+
43
+ | ๐Ÿ—‚๏ธ Data Construction | ๐Ÿ›ก๏ธ AI Trust & Safety | ๐Ÿ“Š Datumo Platform |
44
+ |---|---|---|
45
+ | ๊ณ ๋‚œ๋„ ์ถ”๋ก  ๋ฐ์ดํ„ฐ ์ƒ์„ฑ (CAC-CoT, GRADE, ATA, COBA) | LLM ๋ ˆ๋“œํ‹ฐ๋ฐ (CAGE, STAR-Teaming) | ๊ตญ๋‚ด ์ตœ์ดˆ LLM ์‹ ๋ขฐ์„ฑ ์ž๋™ํ™” ํ‰๊ฐ€ ํ”Œ๋žซํผ |
46
+ | ์‚ฌ์ „ํ•™์ŠตยทํŒŒ์ธํŠœ๋‹ ๋ฐ์ดํ„ฐ ๋ผ์ด์„ ์‹ฑ | ํ•œ๊ตญ์–ด Safety ๋ฒค์น˜๋งˆํฌ (KorNAT, KorSET, FinRED) | **ํ‰๊ฐ€ ๊ธฐ๊ฐ„ 45์ผ โ†’ 45๋ถ„** |
47
+ | RAG ์ง€์‹ ํŒŒ์ดํ”„๋ผ์ธ | Safety Judge (Datumo-Guard) | ์˜จํ”„๋ ˆ๋ฏธ์Šคยท๋ง๋ถ„๋ฆฌ ํ™˜๊ฒฝ ์ง€์› |
48
+ | 25๋งŒ ๋ช…+ ํฌ๋ผ์šฐ๋“œ์›Œ์ปค ยท 2์–ต ๊ฑด+ ์–ด๋…ธํ…Œ์ด์…˜ | ๊ธˆ์œตยท์˜๋ฃŒยท๊ณต๊ณต ๋„๋ฉ”์ธ ํŠนํ™” ํ‰๊ฐ€ | Dashboard Analytics & Reporting |
49
+
50
+ > ๐Ÿค **์ฃผ์š” ํŒŒํŠธ๋„ˆ์‹ญ**: SKT ๋…์ž AI ํŒŒ์šด๋ฐ์ด์…˜ ๋ชจ๋ธ(๋…ํŒŒ๋ชจ) ์ปจ์†Œ์‹œ์—„ ยท GSMA Open Telco AI ยท ์‚ผ์„ฑ์ƒ๋ช… C-Lab Outside ยท ๊ธˆ์œต๋ณด์•ˆ์› ยท ์‹์•ฝ์ฒ˜ ์˜๋ฃŒ ๋ ˆ๋“œํŒ€
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
51
 
52
  ---
53
 
54
  ## ๐Ÿ“š Featured Collections
55
 
56
  ### ๐Ÿ›ก๏ธ [Safety-Data](https://huggingface.co/collections/datumo/safety-data)
57
+
58
  Curated by our **AI Safety team** โ€” Korean-language safety and reliability benchmarks for LLM evaluation.
59
 
60
+ | Dataset | Description | Venue |
61
+ |---|---|---|
62
+ | ๐Ÿ”ธ [**KorSET**](https://huggingface.co/datasets/datumo/KorSET) | CAGE ํ”„๋ ˆ์ž„์›Œํฌ๋กœ ๊ตฌ์ถ•ํ•œ ํ•œ๊ตญ์–ด ๋ ˆ๋“œํ‹ฐ๋ฐ ๋ฒค์น˜๋งˆํฌ (5๊ฐœ ์œ„ํ—˜ ๋„๋ฉ”์ธ ยท 12๊ฐœ ์นดํ…Œ๊ณ ๋ฆฌ ยท 53๊ฐœ ์„ธ๋ถ€ ์œ ํ˜• ยท ~8,000๊ฑด) | **ICLR 2026** (CAGE) |
63
+ | ๐Ÿ”ธ [**KorNAT**](https://huggingface.co/datasets/datumo/KorNAT) | Korea's first LLM reliability / national-alignment benchmark | ACL 2024 Findings |
64
+ | ๐Ÿ”ธ **FinRED** | ๊ธˆ์œต ๋„๋ฉ”์ธ LLM **๋ ˆ๋“œํ‹ฐ๋ฐ(Red-Teaming)** ํ‰๊ฐ€ ๋ฒค์น˜๋งˆํฌ (๊ธˆ์œต๋ณด์•ˆ์› AIํ˜์‹ ์‹ค ๊ณต๋™ ๊ตฌ์ถ•) | KDD 2026 D&B Track |
65
 
66
  ### ๐Ÿ“ฆ [Data-Data](https://huggingface.co/collections/datumo/data-data)
 
67
 
68
+ Research outputs from our **Data team** โ€” models and datasets built in-house.
69
+
70
+ | Resource | Description | Type |
71
+ |---|---|---|
72
+ | ๐Ÿ”ธ [**CAC-CoT**](https://huggingface.co/datumo/CAC-CoT) | 7B Connector-Aware Compact Chain-of-Thought reasoning model | Model |
73
+ | ๐Ÿ”ธ [**CAC-CoT dataset**](https://huggingface.co/datasets/datumo/CAC-CoT) | Accompanying training data for CAC-CoT | Dataset |
74
+
75
+ ### ๐Ÿ—๏ธ Co-built Benchmarks
76
+
77
+ ์…€๋ ‰ํŠธ์Šคํƒ€๊ฐ€ ๊ณต๋™ ๊ตฌ์ถ•์— ์ฐธ์—ฌํ•œ ํ•œ๊ตญ์–ด ๋Œ€ํ‘œ ๋ฒค์น˜๋งˆํฌ์ž…๋‹ˆ๋‹ค.
78
+
79
+ - ๐Ÿ”น [**KLUE**](https://huggingface.co/datasets/klue/klue) โ€” Korean Language Understanding Evaluation (NeurIPS 2021 Datasets & Benchmarks)
80
+ - ๐Ÿ”น [**KorQuAD 2.0**](https://huggingface.co/datasets/KETI-AIR/korquad) โ€” Korean Question Answering Dataset (LG CNS ๊ณต๋™ ๊ตฌ์ถ•)
81
 
82
  > ๐Ÿ’ก ํŒ”๋กœ์šฐํ•˜์‹œ๋ฉด ์ƒˆ ๋ฐ์ดํ„ฐ์…‹๊ณผ ๋ชจ๋ธ์ด ๊ณต๊ฐœ๋  ๋•Œ ์•Œ๋ฆผ์„ ๋ฐ›์œผ์‹ค ์ˆ˜ ์žˆ์–ด์š”.
83
 
 
85
 
86
  ## ๐Ÿ† Milestones
87
 
88
+ **Highlight (์ตœ๊ทผ ์ฃผ์š” ์„ฑ๊ณผ)**
89
+
90
+ - ๐Ÿ… **Forbes "30 Under 30 Asia" 2021** โ€” Enterprise Technology (๊ณต๋™์ฐฝ์—…์ž 4์ธ ์„ ์ •)
91
+ - ๐Ÿ… **Forbes Korea "2025 ๋Œ€ํ•œ๋ฏผ๊ตญ AI 50"** ์„ ์ •
92
+ - ๐Ÿ… **Forbes Asia "100 ์œ ๋ง ๊ธฐ์—…" 2025** ์„ ์ •
93
+ - ๐Ÿ‡ฐ๐Ÿ‡ท **๋…์ž AI ํŒŒ์šด๋ฐ์ด์…˜ ๋ชจ๋ธ(๋…ํŒŒ๋ชจ)** 1์ฐจ ํ†ต๊ณผ (2026.01, SKT ์ปจ์†Œ์‹œ์—„ ๋ฐ์ดํ„ฐ ์ด๊ด„)
94
+ - ๐ŸŒ **GSMA Open Telco AI** ๊ณต์‹ ํŒŒํŠธ๋„ˆ ํ•ฉ๋ฅ˜ (2026.03, MWC Barcelona)
95
+ - ๐Ÿ’ฐ ๋ˆ„์  ํˆฌ์ž **434์–ต์› ๋ŒํŒŒ** (2025.12, Series B ํ™•์žฅ)
96
+ - ๐Ÿ“ˆ ๋ˆ„์  ์–ด๋…ธํ…Œ์ด์…˜ **2์–ต ๊ฑด+** ยท ๊ธฐ์—… ๊ณ ๊ฐ **287๊ฐœ+** ยท ํฌ๋ผ์šฐ๋“œ์›Œ์ปค **25๋งŒ ๋ช…+**
97
+
98
+ <details>
99
+ <summary><b>๐Ÿ“œ ์ „์ฒด ์—ฐํ˜ ๋ณด๊ธฐ (2018โ€“2026)</b></summary>
100
+
101
+ ### ๐ŸŒฑ Founding & Early Traction (2018โ€“2020)
102
+
103
+ | ์—ฐ์›” | ๋‚ด์šฉ |
104
+ |---|---|
105
+ | 2018.11 | ์…€๋ ‰ํŠธ์Šคํƒ€(์ฃผ) ์„ค๋ฆฝ |
106
+ | 2018.12 | KAIST ์ฐฝ์—…๋Œ€ํšŒ(E*5) ์ตœ์šฐ์ˆ˜์ƒ |
107
+ | 2019.07 | ์นด์นด์˜ค๋ฒค์ฒ˜์Šค SEED 4์–ต ํˆฌ์ž ์œ ์น˜ |
108
+ | 2019.09 | KorQuAD 2.0 Dataset ๊ตฌ์ถ• (LG CNS ๊ณต๋™) |
109
+ | 2019.10 | TIPS ํ”„๋กœ๊ทธ๋žจ ์„ ์ • |
110
+ | 2019.12 | ๊ธฐ์—…๋ถ€์„ค์—ฐ๊ตฌ์†Œ ์„ค๋ฆฝ ์ธ์ • |
111
+ | 2020.09 | Series A 40์–ต ํˆฌ์ž ์œ ์น˜ (์นด์นด์˜ค๋ฒค์ฒ˜์Šคยท์ฝ”์˜ค๋กฑ์ธ๋ฒ ์ŠคํŠธ๋จผํŠธยท์ปดํผ๋‹ˆ์ผ€์ดํŒŒํŠธ๋„ˆ์Šค) |
112
+ | 2020.10 | **SideGuide** (IROS 2020) ๋…ผ๋ฌธ ์„ฑ๊ณผ โ€” Large-scale Sidewalk Dataset |
113
+ | 2020.11 | ๋ฐ์ดํ„ฐ์Šคํƒ€์ฆˆ ์ตœ์šฐ์ˆ˜์ƒ (๊ณผํ•™๊ธฐ์ˆ ์ •๋ณดํ†ต์‹ ๋ถ€์žฅ๊ด€์ƒ) |
114
+
115
+ ### ๐Ÿš€ Scale-Up & Global Recognition (2021โ€“2022)
116
+
117
+ | ์—ฐ์›” | ๋‚ด์šฉ |
118
+ |---|---|
119
+ | 2021.01 | Samsung C-Lab Outside ์„ ์ • |
120
+ | **2021.04** | ๐Ÿ… **Forbes "30 Under 30 Asia"** Enterprise Technology ์„ ์ • (๊ณต๋™์ฐฝ์—…์ž 4์ธ) |
121
+ | 2021.11 | **KLUE** NeurIPS 2021 Datasets & Benchmarks ๋…ผ๋ฌธ ์„ฑ๊ณผ |
122
+ | 2022.01 | CES 2022 ์ฐธ์—ฌ (Samsung C-Lab) |
123
+ | 2022.02 | ์ œ1๊ธฐ ์ธ๊ณต์ง€๋Šฅ ์œค๋ฆฌ ์ •์ฑ… ํฌ๋Ÿผ ๊ธฐ์ˆ  ๋ถ„๊ณผ ์œ„์› ์„ ์ • |
124
+ | 2022.03 | **Instance-wise Occlusion and Depth Orders** CVPR 2022 ๋…ผ๋ฌธ ์„ฑ๊ณผ |
125
+ | 2022.07 | Series A Extension 90์–ต ํˆฌ์ž ์œ ์น˜ |
126
+ | 2022.07 | ๊ธฐ์ˆ ํ˜์‹ ํ˜• ์ค‘์†Œ๊ธฐ์—…(inno-Biz) ์ธ์ฆ |
127
+ | 2022.11 | **KOLD** (EMNLP 2022), **CochlScene** (APSIPA 2022), **Split-GCN** (TPAMI, 1์ €์ž) ๋…ผ๋ฌธ ์„ฑ๊ณผ |
128
+
129
+ ### ๐Ÿง  LLM Era & AI Safety (2023โ€“2024)
130
+
131
+ | ์—ฐ์›” | ๋‚ด์šฉ |
132
+ |---|---|
133
+ | 2023.05 | Series A Extension 40์–ต ํˆฌ์ž ์œ ์น˜ (์‚ฐ์—…์€ํ–‰) |
134
+ | 2023.06 | AI ๊ธฐ๋ฐ˜ ๊ตญ๋ฐฉ ํ˜์‹  ํฌ๋Ÿผ ๋Œ€์ƒ (์œก๊ตฐ์ฐธ๋ชจ์ด์žฅ์ƒ) |
135
+ | 2023.07 | "AI Talk with Andrew Ng" ํ–‰์‚ฌ Keynote Speaker |
136
+ | 2023.10 | Samsung Developer Conference 2023 ์—ฐ์‚ฌ ์ฐธ์—ฌ |
137
+ | 2023.11 | ๋Œ€ํ•œ๋ฏผ๊ตญ Digital Innovation Award ํŠน๋ณ„์ƒ |
138
+ | 2023.12 | **Analyzing Norm Violations in Live-Stream Chat** EMNLP 2023 ๋…ผ๋ฌธ ์„ฑ๊ณผ |
139
+ | 2023.12 | ๊ตญ๋‚ด ์ตœ์ดˆ "์ดˆ๊ฑฐ๋Œ€ ์–ธ์–ด ๋ชจ๋ธ ์‹ ๋ขฐ์„ฑ ๋ฒค์น˜๋งˆํฌ ๋ฐ์ดํ„ฐ์…‹" ๊ตฌ์ถ• (NIA) |
140
+ | 2024.04 | **Gen AI Korea 2024: ์ƒ์„ฑํ˜• AI ๋ ˆ๋“œํŒ€ ์ฑŒ๋ฆฐ์ง€** ์ปจํผ๋Ÿฐ์Šค ๊ธฐํšยท์šด์˜ (๊ณผ๊ธฐ์ •ํ†ต๋ถ€) |
141
+ | **2024.08** | **KorNAT** ACL 2024 Findings ๋…ผ๋ฌธ ์„ฑ๊ณผ โ€” ๊ตญ๋‚ด AI ๋ฐ์ดํ„ฐ ๊ธฐ์—… ์ตœ์ดˆ ๊ธ€๋กœ๋ฒŒ Top AI ํ•™ํšŒ ๋ฐ์ดํ„ฐ์…‹ 1์ €์ž ๋…ผ๋ฌธ |
142
+ | 2024.10 | KT 'Responsible AI ์ž๋ฌธ ์œ„์›ํšŒ' ์ž๋ฌธ์œ„ ์œ„์› ์„ ์ • |
143
+ | 2024.11 | ์ œ2ํšŒ ์ธ๊ณต์ง€๋Šฅ ์‹ ๋ขฐ์„ฑ ๋Œ€์ƒ ์šฐ์ˆ˜์ƒ (์ •๋ณดํ†ต์‹ ์ •์ฑ…์—ฐ๊ตฌ์› ์›์žฅ์ƒ) |
144
+ | 2024.11 | GSMA AI Summit 2024 ์—ฐ์‚ฌ ์ฐธ์—ฌ |
145
+ | 2024.12 | ๊ตญ๋‚ด ์ตœ์ดˆ **LLM ๋ฌดํ•ด์„ฑ ํ‰๊ฐ€ ๋ฐ์ดํ„ฐ DQ(Data Quality) ์ธ์ฆ** ํš๋“ (TTA) |
146
+ | 2024.12 | 2024 ์•„์‹œ์•„AI๋Œ€์ƒ ๋ฒค์ฒ˜๊ธฐ์—…ํ˜‘ํšŒ ํšŒ์žฅ์ƒ |
147
+
148
+ ### ๐ŸŒ Agentic AI & Global Expansion (2025โ€“2026)
149
+
150
+ | ์—ฐ์›” | ๋‚ด์šฉ |
151
+ |---|---|
152
+ | 2025.02 | **Datumo Eval ์ถœ์‹œ** โ€” ๊ตญ๋‚ด ์ตœ์ดˆ LLM ์ž๋™ํ™” ํ‰๊ฐ€ ํ”Œ๋žซํผ |
153
+ | 2025.03 | **Gen AI Red Team Challenge** ๊ณต๋™ ๊ฐœ์ตœ (MWC Barcelona, GSMA) โ€” ์„ธ๊ณ„ ์ตœ์ดˆ ์˜คํ”„๋ผ์ธ ๊ธ€๋กœ๋ฒŒ ๋ ˆ๋“œํŒ€ ์ฑŒ๋ฆฐ์ง€ |
154
+ | 2025.04 | AI ๊ธฐ๋ณธ๋ฒ• ์•ˆ์ „์„ฑ ๊ฐ€์ด๋“œ๋ผ์ธ TF ์œ„์› ์„ ์ • (๊ณผ๊ธฐ์ •ํ†ต๋ถ€ยทAI์•ˆ์ „์—ฐ๊ตฌ์†Œ, ๊น€์„ธ์—ฝ ๋Œ€ํ‘œ) |
155
+ | 2025.05 | ๐Ÿ… **Forbes Korea "2025 ๋Œ€ํ•œ๋ฏผ๊ตญ AI 50"** ์„ ์ • |
156
+ | 2025.06 | ์‚ผ์„ฑ๊ธˆ์œต C-Lab Outside ์ตœ์ข… ์„ ์ • (์‚ผ์„ฑ์ƒ๋ช… ๊ธˆ์œต AI ์‹ ๋ขฐ์„ฑ ๊ฒ€์ฆ ํ˜‘์—…) |
157
+ | 2025.07 | ๋ฏผ๊ฐ„ AI ์‹ ๋ขฐ์„ฑ ์ธ์ฆ 'AI-MASTER' ์‹œํ—˜๊ธฐ๊ด€ ์ฐธ์—ฌ (๊ตญ๋‚ด ์ตœ์ดˆ ๋ฏผ๊ฐ„ ์ฃผ๋„ ์ฒด๊ณ„) |
158
+ | 2025.08 | **Series B 205์–ต์› ํˆฌ์ž ์œ ์น˜** |
159
+ | 2025.08 | ๐Ÿ… **Forbes Asia "100 ์œ ๋ง ๊ธฐ์—… 2025"** ์„ ์ • |
160
+ | 2025.08 | **๋…์ž AI ํŒŒ์šด๋ฐ์ด์…˜ ๋ชจ๋ธ(๋…ํŒŒ๋ชจ)** ์ •์˜ˆํŒ€ ์„ ๋ฐœ (SKT ์ปจ์†Œ์‹œ์—„ ๋ฐ์ดํ„ฐ ์ด๊ด„) |
161
+ | 2025.09 | **๊ตญ๊ฐ€์ธ๊ณต์ง€๋Šฅ์ „๋žต์œ„์›ํšŒ ๋ฐ์ดํ„ฐ ๋ถ„๊ณผ์œ„์›** ์œ„์ด‰ (๊น€์„ธ์—ฝ ๋Œ€ํ‘œ) |
162
+ | 2025.09 | ์‹์•ฝ์ฒ˜ ์ฒจ๋‹จ AI ๋””์ง€ํ„ธ ์˜๋ฃŒ์ œํ’ˆ ๋ ˆ๋“œํŒ€ ์ฑŒ๋ฆฐ์ง€ ํ›„์› โ€” ์•„์‹œ์•„ ์ฒซ '์˜๋ฃŒ ๋ ˆ๋“œํŒ€' |
163
+ | 2025.10 | ์‚ผ์„ฑ๊ธˆ์œต C-Lab Outside **์ตœ์šฐ์ˆ˜ ์Šคํƒ€ํŠธ์—…** ์„ ์ • (์‚ผ์„ฑ์ƒ๋ช…) |
164
+ | 2025.11 | **CAC-CoT ยท CoBA ยท GRADE** EMNLP 2025 ๋…ผ๋ฌธ 3ํŽธ ๋™์‹œ ๋“ฑ์žฌ |
165
+ | 2025.11 | 2025 ์ด๋ฐ์ผ๋ฆฌ AI ์ฝ”๋ฆฌ์•„ ๋Œ€์ƒ (ํ•œ๊ตญ์ธ๊ณต์ง€๋Šฅ์‚ฐ์—…ํ˜‘ํšŒ์žฅ์ƒ) |
166
+ | 2025.11 | Good AI Awards 2025 NIA ์›์žฅ์ƒ |
167
+ | 2025.12 | Series B 55์–ต์› ์ถ”๊ฐ€ ํˆฌ์ž โ€” **๋ˆ„์  ํˆฌ์ž 434์–ต์›** ๋ŒํŒŒ |
168
+ | **2026.01** | ๐Ÿ‡ฐ๐Ÿ‡ท **๋…์ž AI ํŒŒ์šด๋ฐ์ด์…˜ ๋ชจ๋ธ(๋…ํŒŒ๋ชจ) 1์ฐจ ํ†ต๊ณผ** (SKT ์ปจ์†Œ์‹œ์—„) |
169
+ | 2026.02 | **CAGE** ICLR 2026 Main Conference ๋…ผ๋ฌธ ์„ฑ๊ณผ |
170
+ | 2026.03 | **GSMA 'Open Telco AI'** ๊ธ€๋กœ๋ฒŒ ์—ฐํ•ฉ์ฒด ๊ณต์‹ ํŒŒํŠธ๋„ˆ ํ•ฉ๋ฅ˜ (MWC Barcelona) |
171
+ | 2026.03 | MWC 2026 Gen AI Red Team Challenge ๊ณต๋™ ์ฃผ๊ด€ (GSMA ยท LG U+) |
172
+
173
+ </details>
174
+
175
+ ---
176
+
177
+ ## ๐Ÿ“– Publications
178
+
179
+ ์…€๋ ‰ํŠธ์Šคํƒ€๊ฐ€ ๋‹จ๋…ยท๊ณต๋™ยท์ง€์› ์ฐธ์—ฌํ•œ ๋…ผ๋ฌธ ๋ชฉ๋ก์ž…๋‹ˆ๋‹ค. ๊ตญ์ œ AIยทML Top ํ•™ํšŒ ์ค‘๏ฟฝ๏ฟฝ๏ฟฝ์œผ๋กœ ์ •๋ฆฌํ–ˆ์Šต๋‹ˆ๋‹ค.
180
+
181
+ <details open>
182
+ <summary><b>๐Ÿ”ฅ 2026 (4ํŽธ)</b></summary>
183
+
184
+ | Paper | Co-authors | Venue |
185
+ |---|---|---|
186
+ | **STAR-Teaming**: A Strategy-Response Multiplex Network Approach to Automated LLM Red Teaming | Selectstar | ACL 2026 |
187
+ | **FinRED**: An Expert-Guided Red-Teaming Benchmark for Financial LLM Safety | Selectstar ยท ๊ธˆ์œต๋ณด์•ˆ์› AIํ˜์‹ ์‹ค | KDD 2026 Dataset & Benchmark Track |
188
+ | [**CAGE**](https://openreview.net/forum?id=gCm55KYiqz): A Framework for Culturally Adaptive Red-Teaming Benchmark Generation | Selectstar | **ICLR 2026** Main |
189
+ | **E-star-12B**: Rubric-Following Evaluator Adaptive Across Industrial Domains | Selectstar | ACL 2026 Workshop (์ง„ํ–‰ ์ค‘) |
190
+
191
+ </details>
192
+
193
+ <details>
194
+ <summary><b>๐Ÿ“„ 2025 (4ํŽธ)</b></summary>
195
+
196
+ | Paper | Co-authors | Venue |
197
+ |---|---|---|
198
+ | [**CoBA**](https://aclanthology.org/2025.emnlp-main.520/): Counterbias Text Augmentation for Mitigating Various Spurious Correlations via Semantic Triples | Selectstar ยท ์ค‘์•™๋Œ€ํ•™๊ต | EMNLP 2025 Main |
199
+ | [**GRADE**](https://aclanthology.org/2025.findings-emnlp.236/): Generating multi-hop QA and fine-gRAined Difficulty matrix for RAG Evaluation | Selectstar ยท KAIST | EMNLP 2025 Findings |
200
+ | [**CAC-CoT**](https://aclanthology.org/2025.findings-emnlp.1062/): Connector-Aware Compact Chain-of-Thought for Efficient Reasoning Data Synthesis Across Dual-System Cognitive Tasks | Selectstar | EMNLP 2025 Findings |
201
+ | **ATA**: Autonomous Tabular-data Analysis for Insight Generation via Statistical Methods | Selectstar ยท ์‚ผ์„ฑ์ฆ๊ถŒ ๊ธˆ์œตAI์„ผํ„ฐ | ๊ณต์ € ์ œ์ถœ ์ค‘ |
202
+
203
+ </details>
204
+
205
+ <details>
206
+ <summary><b>๐Ÿ“„ 2024 (1ํŽธ)</b></summary>
207
+
208
+ | Paper | Co-authors | Venue |
209
+ |---|---|---|
210
+ | [**KorNAT**](https://arxiv.org/abs/2402.13605): LLM Alignment Benchmark for Korean Social Values and Common Knowledge | Selectstar ยท KAIST ยท SKT ยท LG ยท ๋„ค์ด๋ฒ„ ยท KT ยท NIA | ACL 2024 Findings |
211
+
212
+ > ๊ตญ๋‚ด AI ๋ฐ์ดํ„ฐ ๊ธฐ์—… ์ตœ์ดˆ ๊ธ€๋กœ๋ฒŒ Top AI ํ•™ํšŒ์— ๋ฐ์ดํ„ฐ์…‹ ์ฃผ์ œ 1์ €์ž ๋…ผ๋ฌธ ๋“ฑ์žฌ
213
+
214
+ </details>
215
+
216
+ <details>
217
+ <summary><b>๐Ÿ“„ 2021โ€“2023 (5ํŽธ)</b></summary>
218
+
219
+ | Year | Paper | Venue |
220
+ |---|---|---|
221
+ | 2023 | [**Analyzing Norm Violations in Live-Stream Chat**](https://aclanthology.org/2023.emnlp-main.55/) | EMNLP 2023 |
222
+ | 2022 | [**KOLD**](https://aclanthology.org/2022.emnlp-main.744/): Korean Offensive Language Dataset | EMNLP 2022 |
223
+ | 2022 | [**Split-GCN**](https://ieeexplore.ieee.org/document/9984937): Effective Interactive Annotation for Segmentation of Disconnected Instance | IEEE TPAMI (1์ €์ž) |
224
+ | 2022 | [**Instance-wise Occlusion and Depth Orders**](https://openaccess.thecvf.com/content/CVPR2022/html/Lee_Instance-Wise_Occlusion_and_Depth_Orders_in_Natural_Scenes_CVPR_2022_paper.html) | CVPR 2022 |
225
+ | 2022 | [**CochlScene**](https://ieeexplore.ieee.org/document/9979822): Acquisition of acoustic scene data using crowdsourcing | APSIPA 2022 |
226
+ | 2021 | [**KLUE**](https://datasets-benchmarks-proceedings.neurips.cc/paper/2021/hash/98dce83da57b0395e163467c9dae521b-Abstract-round2.html): Korean Language Understanding Evaluation | NeurIPS 2021 Datasets & Benchmarks |
227
+ | 2020 | [**SideGuide**](https://ieeexplore.ieee.org/document/9340734): A Large-scale Sidewalk Dataset for Guiding Impaired People | IROS 2020 |
228
+
229
+ </details>
230
+
231
+ > ์ „์ฒด ๋…ผ๋ฌธ ๋ชฉ๋ก ๋ฐ ์ƒ์„ธ ๋‚ด์šฉ์€ [๋ธ”๋กœ๊ทธ](https://selectstar.ai/blog/) ๋˜๋Š” [๋ฌธ์˜ํ•˜๊ธฐ](https://selectstar.ai/contact_page/)๋ฅผ ํ†ตํ•ด ํ™•์ธํ•˜์‹ค ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.
232
 
233
  ---
234
 
 
239
  | ๐ŸŒ Website | [selectstar.ai](https://selectstar.ai/) |
240
  | ๐Ÿ“ฐ Blog | [selectstar.ai/blog](https://selectstar.ai/blog/) |
241
  | ๐Ÿ’ผ Enterprise inquiries | [Contact form](https://selectstar.ai/contact_page/) |
242
+ | ๐Ÿ’ฌ Community | [Discussion tab](https://huggingface.co/spaces/datumo/README/discussions) |
243
+ | ๐Ÿ”” Updates | HuggingFace ํŒ”๋กœ์šฐ๋กœ ์ƒˆ ๋ฆด๋ฆฌ์ฆˆ ์•Œ๋ฆผ ๋ฐ›๊ธฐ |
244
 
245
  ---
246
 
247
  <div align="center">
248
+ <sub>โญ Building the data foundation for trustworthy AI ยท Made with care in Seoul ๐Ÿ‡ฐ๐Ÿ‡ท</sub>
249
  </div>