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Changdae Oh

@changdaeoh.bsky.social

CS PhD Student @ UW-Madison Distribution Shifts, Uncertainty Quantification, Multimodal, LLM Agents Prev: NAVER AI Lab, CMU, USeoul changdaeoh.github.io

Posts Replies Media

Changdae Oh @changdaeoh.bsky.social · 07/02/2026

Have been cooking with so many amazing professionals, Seongheon Park, @teknology.bsky.social , Jiatong Li, Wendi Li, Samuel Yeh, Xuefeng Du, Hamed Hassani, @paulbogdan.bsky.social , Dawn Song, and Sharon Li🥰 Truly enjoyed it and learned a lot🙏

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Changdae Oh @changdaeoh.bsky.social · 07/02/2026

We tend to conflate "autonomy" with "reliability" in AI agents. But autonomy without trust is catastrophically dangerous. Our new paper formalizes UQ for LLM agents, proposes a new lens: agent uncertainty as a conditional uncertainty reduction process. 📄 huggingface.co/papers/2602....

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Reposted by Changdae Oh

Danny To Eun Kim @teknology.bsky.social · 09/12/2024

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

arxiv.org

Towards Fair RAG: On the Impact of Fair Ranking in Retrieval-Augmented Generation

Many language models now enhance their responses with retrieval capabilities, leading to the widespread adoption of retrieval-augmented generation (RAG) systems. However, despite retrieval being a cor...

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