Papers by Jingyi Ren

2 papers
Beyond "I Don’t Know": Evaluating LLM Self-Awareness in Discriminating Data and Model Uncertainty (2026.acl-long)

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Challenge: Prior studies treat refusal as a generic "I don't know" lack of distinction limits downstream action decisions like requesting clarification or invoking external tools.
Approach: They propose a benchmark to evaluate explicit uncertainty attribution in large language models.
Outcome: The proposed method improves uncertainty attribution while preserving answer accuracy.
UR2 : Unify RAG and Reasoning through Reinforcement Learning (2026.acl-long)

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Challenge: Existing attempts to unify large language models are limited to open-domain QA with fixed retrieval settings.
Approach: They propose a general reinforcement learning framework that dynamically coordinates retrieval and reasoning.
Outcome: The proposed framework outperforms existing paradigms on open-domain QA, MMLU-Pro, medical, and mathematical reasoning tasks.

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