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cs.CL2026
Mitigating Bias in Locally Constrained Decoding via Tractable Proposals
Meihua Dang, Linxin Song, Honghua Zhang +3
Generations from large language models often fail to conform to desired constraints such as JSON schema. Existing locally constrained decoding (LCD) approaches enforce constraints…
cs.CL2025
The Hallucination Tax of Reinforcement Finetuning
Linxin Song, Taiwei Shi, Jieyu Zhao
Reinforcement finetuning (RFT) has become a standard approach for enhancing the reasoning capabilities of large language models (LLMs). However, its impact on model trustworthiness…
cs.CL2023★ 3 cited
Safer-Instruct: Aligning Language Models with Automated Preference Data
Taiwei Shi, Kai Chen, Jieyu Zhao
Reinforcement learning from human feedback (RLHF) is a vital strategy for enhancing model capability in language models. However, annotating preference data for RLHF is a resource-…