3 papers
cs.LG2026
AREAL-DTA: Dynamic Tree Attention for Efficient Reinforcement Learning of Large Language Models
Jiarui Zhang, Yuchen Yang, Ran Yan +8
Reinforcement learning (RL)-based post-training for large language models (LLMs) is computationally expensive, as it generates many rollout sequences that frequently share long tok…
cs.DC2026
ARGUS: Agentic GPU Optimization Guided by Data-Flow Invariants
Haohui Mai, Xiaoyan Guo, Xiangyun Ding +7
LLM-based coding agents can generate functionally correct GPU kernels, yet their performance remains far below hand-optimized libraries on critical computations such as matrix mult…
cs.CL2025
ChatGPT is not A Man but Das Man: Representativeness and Structural Consistency of Silicon Samples Generated by Large Language Models
Dai Li, Linzhuo Li, Huilian Sophie Qiu
Large language models (LLMs) in the form of chatbots like ChatGPT and Llama are increasingly proposed as "silicon samples" for simulating human opinions. This study examines this n…