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20232026
most citedHAE-RAE Bench: Evaluation of Korean Knowledge in Language Models

1 citations · 1 across the 13 of their papers we have counts for

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cs.CL2026

Disentangling Question, Response, and Verifier Languages in Multilingual P(True) Self-Evaluation

Jewon Yeom, Jaewon Sok, Seonghyeon Park +3

When a language model is asked whether its own answer is correct, three languages are involved: that of the question, that requested for the answer, and that of the verifier instru…

cs.CL2026

Answer First, Reason Later: When Commitment Order Costs Accuracy in Diffusion Language Models

Jewon Yeom, Jaewon Sok, Seonghyeon Park +3

Masked diffusion language models revise many masked output positions in parallel. We call a token committed once it becomes visible and is never masked again, and call a response a…

cs.CL2026

Hallucination as Commitment Failure: Larger LLMs Misfire Despite Knowing the Answer

Jewon Yeom, Jaewon Sok, Heejun Kim +3

Hallucination is often viewed as a direct consequence of missing knowledge: a model answers incorrectly when the correct answer is absent from its generation-time distribution, and…

cs.CL2026

Garbage Attention in Large Language Models: BOS Sink Heads and Sink-aware Pruning

Jaewon Sok, Jewon Yeom, Seonghyeon Park +2

Large Language Models (LLMs) are known to contain significant redundancy, yet a systematic explanation for why certain components, particularly in higher layers, are more redundant…

cs.CL2026

EpiCaR: Knowing What You Don't Know Matters for Better Reasoning in LLMs

Jewon Yeom, Jaewon Sok, Seonghyeon Park +2

Improving the reasoning abilities of large language models (LLMs) has largely relied on iterative self-training with model-generated data. While effective at boosting accuracy, exi…

cs.CL2025

"Well, Keep Thinking": Enhancing LLM Reasoning with Adaptive Injection Decoding

Hyunbin Jin, Je Won Yeom, Seunghyun Bae +1

Large language models (LLMs) exhibit strong reasoning abilities, often attributed to few-shot or zero-shot chain-of-thought (CoT) prompting. While effective, these methods require…

cs.CL2023★ 1 cited

HAE-RAE Bench: Evaluation of Korean Knowledge in Language Models

Guijin Son, Hanwool Lee, Suwan Kim +6

Large language models (LLMs) trained on massive corpora demonstrate impressive capabilities in a wide range of tasks. While there are ongoing efforts to adapt these models to langu…