1 citations · 1 across the 4 of their papers we have counts for
5 papers
Learning Perturbation-Specific Representations through Conditional Energy Prior for Cellular Response Prediction
Yuchen Yan, Yatao Bian
AI-based cellular perturbation prediction is essential to accelerate drug discovery and therapeutic identification. However, perturbation-specific signals are generally obscured by…
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…
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…
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…
Integration of cognitive tasks into artificial general intelligence test for large models
Youzhi Qu, Chen Wei, Penghui Du +10
During the evolution of large models, performance evaluation is necessarily performed to assess their capabilities and ensure safety before practical application. However, current…