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cs.CL2026

SimSD: Simple Speculative Decoding in Diffusion Language Models

Junxia Cui, Haotian Ye, Runchu Tian +9

Diffusion large language models (dLLMs) have recently emerged as a promising alternative to autoregressive (AR) LLMs, offering faster inference through parallel or blockwise decodi…

cs.CL2026

BOOKMARKS: Efficient Active Storyline Memory for Role-playing

Letian Peng, Ziche Liu, Yiming Huang +4

Memory systems are critical for role-playing agents (RPAs) to maintain long-horizon consistency. However, existing RPA memory methods (e.g., profiling) mainly rely on recurrent sum…

cs.CL2026

Adapt to Thrive! Adaptive Power-Mean Policy Optimization for Improved LLM Reasoning

Yiming Huang, Zhenbo Shi, Shuzheng Gao +3

Reinforcement Learning with Verifiable Rewards (RLVR) is an essential paradigm that enhances the reasoning capabilities of Large Language Models (LLMs). However, existing methods t…

cs.CL2026

Free Energy-Driven Reinforcement Learning with Adaptive Advantage Shaping for Unsupervised Reasoning in LLMs

Yiming Huang, Zhenbo Shi, Xin-Cheng Wen +4

Unsupervised reinforcement learning (RL) has emerged as a promising paradigm for enabling self-improvement in large language models (LLMs). However, existing unsupervised RL-based…

cs.CL2026

Understanding the Anchoring Effect of LLM with Synthetic Data: Existence, Mechanism, and Potential Mitigations

Yiming Huang, Biquan Bie, Zuqiu Na +4

The rise of Large Language Models (LLMs) like ChatGPT has advanced natural language processing, yet concerns about cognitive biases are growing. In this paper, we investigate the a…

cs.CL2026

RePPL: Recalibrating Perplexity by Uncertainty in Semantic Propagation and Language Generation for Explainable QA Hallucination Detection

Yiming Huang, Junyan Zhang, Zihao Wang +5

Large Language Models (LLMs) have become powerful, but hallucinations remain a vital obstacle to their trustworthy use. Previous works improved the capability of hallucination dete…