3 papers
cs.AI2026
Escaping Confidence Trap: Evolutionary Decoding for Mathematical Reasoning in Diffusion LLMs
Zhenhong Sun, Hanqing Zhao, Yatao Bian +7
Diffusion large language models (dLLMs) have emerged as a promising alternative to autoregressive LLMs, offering efficient generation through block-wise progressive unmasking. Howe…
cs.CL2026
Unified Energy for Invariant and Independent Decoding in Diffusion Language Models
Yuchen Yan, Minkai Xu, Zaiquan Yang +1
Diffusion Language Models (DLMs) enable parallel text generation by iteratively denoising a full sequence, offering attractive flexibility compared to auto-regressive (AR) decoding…
cs.LG2026
A Survey of Reinforcement Learning for Large Language Models under Data Scarcity: Challenges and Solutions
Zhiyin Yu, Yuchen Mou, Juncheng Yan +17
Reinforcement learning (RL) has emerged as a powerful post-training paradigm for enhancing the reasoning capabilities of large language models (LLMs). However, reinforcement learni…