Danny To Eun Kim
PhD student @CMU LTI
NLP | IR | Evaluation | RAG
https://kimdanny.github.io
- Reposted by Danny To Eun Kim🎭 How do LLMs (mis)represent culture? 🧮 How often? 🧠 Misrepresentations = missing knowledge? spoiler: NO! At #CHI2026 we are bringing ✨TALES✨ a participatory evaluation of cultural (mis)reps & knowledge in multilingual LLM-stories for India 📜 arxiv.org/abs/2511.21322 1/10
- #ChatGPT began to put ads in their response. Check our paper on “how fair ranking can positively impact the LLM response and content/ad exposure”. dl.acm.org/doi/10.1145/...
- as AI increasingly supports shopping and ads, it’s worth remembering that retrieval often shapes who gets exposure in final generated output. in a recent paper, @teknology.bsky.social uses methods from fair ranking to assess and address exposure bias in downstream generation. 841.io/doc/fairrag....
- #chatGPT began to put ads in their response. Check out our paper on “Ads detection and integration in the era of LLMs”. ceur-ws.org/Vol-4038/pap...
- Reposted by Danny To Eun Kimas AI increasingly supports shopping and ads, it’s worth remembering that retrieval often shapes who gets exposure in final generated output. in a recent paper, @teknology.bsky.social uses methods from fair ranking to assess and address exposure bias in downstream generation. 841.io/doc/fairrag....
- Excited to present at #CLEF2025 #Touché Lab (Session 2) shared task "Advertisement in RAG"🇪🇸! @webis.de 🗓️Sept 9 (Tue) ⏲️5:20PM (CEST) / 11:20AM (EST) 📍Florentino Sanz Room 🧠https://arxiv.org/abs/2507.00509 Join us for insights on #RAG + advertising!
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- This year's TREC Tip of the Tongue (ToT) track will be amazing! Based on our rigorous experiments on synthetic ToT query generation presented at #SIGIR2025, we extended the track to open domain ToT queries. We provide codes for baseline systems, and submissions are due by August 27th!
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- ❓How do LLMs respond to fair ranking in RAG? 🤩 See how fair ranking boosts downstream utility while promoting fairer attribution of cited sources. Catch our oral presentation at #ICTIR2025! #SIGIR2025 @841io.bsky.social
- Heading to #NeurIPS2024 to present our ‘Fair RAG’ paper at the #AFME2024 workshop! Let's talk about RAG, Information Retrieval, and Fairness. Honored that our paper was selected as one of the Top 5 Spotlight Papers! 🎉 Let’s connect and chat! Paper: arxiv.org/abs/2409.11598
- Reposted by Danny To Eun KimDo not forget to participate in the #TREC2025 Tip-of-the-Tongue (ToT) Track :) The corpus and baselines (with run files) are now available and easily accessible via the ir_datasets API and the HuggingFace Datasets API. More details are available at: trec-tot.github.io/guidelines
- Reposted by Danny To Eun Kim🖋️ Curious how writing differs across (research) cultures? 🚩 Tired of “cultural” evals that don't consult people? We engaged with interdisciplinary researchers to identify & measure ✨cultural norms✨in scientific writing, and show that❗LLMs flatten them❗ 📜 arxiv.org/abs/2506.00784 [1/11]
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- Reposted by Danny To Eun KimIf you're interested in OpenAI including shopping results, you might also be interested in @teknology.bsky.social's paper relating retrieval diversity/fairness and generation by downstream RAG models. This has implications for individuals selling products online. arxiv.org/abs/2409.11598
- Reposted by Danny To Eun KimIf you're working on a recall-oriented task or with ranking systems evaluated across varied users, content, or intents, check it out. 5/5 dl.acm.org/doi/10.1145/...
- Reposted by Danny To Eun Kim📢 New Paper: "Recall, Robustness, and Lexicographic Evaluation" (ACM TORS) F Diaz, M Ekstrand (@md.ekstrandom.net), B Mitra (@bmitra.bsky.social) For IR, NLP, and ML researchers working on ranking systems evaluated for recall and robustness. 🧵 1/5 dl.acm.org/doi/10.1145/...
- 🚨New Breakthrough in Tip-of-the-Tongue (TOT) Retrieval Research! We address data limitations and offer a fresh evaluation method for these complex queries. Curious how TREC TOT track test queries are created? Check out this thread 🧵 and our paper 📄: arxiv.org/abs/2502.17776
- 👅Tip-of-the-Tongue (TOT) search is a complex form of known-item search, shaped by the expression of partial recall, personal context, and uncertain memories. However, TOT research has long been hindered by the scarcity of high-quality TOT queries.
- 🤔Why the Problem? TOT query data collection relies heavily on community question answering websites (e.g., Reddit). This causes data availability issues and domain bias (most TOT queries end up being about movies or books).
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View full threadHere's an overview of TREC 2024 TOT track runs with the test queries: trec.nist.gov/pubs/trec33/...
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- Heading to #NeurIPS2024 to present our ‘Fair RAG’ paper at the #AFME2024 workshop! Let's talk about RAG, Information Retrieval, and Fairness. Honored that our paper was selected as one of the Top 5 Spotlight Papers! 🎉 Let’s connect and chat! Paper: arxiv.org/abs/2409.11598
- Those who are attending #SIGIRAP2024, come by and learn how retrieval can enhance ML models!
- Link to the website: retrieval-enhanced-ml.github.io/sigir-ap2024...
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- Reposted by Danny To Eun KimTime for a starter pack on information retrieval: go.bsky.app/MXPJoTnat://did:plc:fr4mrqeybprbevl5eenagk5f/app.bsky.graph.starterpack/3lawqgkwp2z25
- Reposted by Danny To Eun KimHey all! I started a second starter pack with people who didn't make the first one, please let me know if you'd like to be added: go.bsky.app/JgneRQkat://did:plc:tj7jc54fic4zlahv4qfmg7mq/app.bsky.graph.starterpack/3las2wmbj2e2s
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