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Paper Accepted to EMNLP 2026 Main Conference

First-authored by our Ph.D. student Hao An, the paper proposes FiSCoRe, jointly fine-tuning models with correctness and semantic-entropy uncertainty.

Good news before the new semester: one paper has been accepted to the EMNLP 2026 Main Conference, first-authored by our Ph.D. student Hao An.

Teaching LLMs to Abstain via Fine-Grained Semantic Confidence Reward (FiSCoRe)

Standing out from last year’s fierce competition in RL fine-tuning for mitigating LLM hallucinations was not easy. Our core contribution — jointly fine-tuning the model with correctness and semantic-entropy uncertainty — remains of long-term value.

Arxiv: https://arxiv.org/abs/2510.24020

Wish everyone a pleasant trip to Budapest!