5 papers
AlphaDiana: A Measurement System for Agents in Verifiable Reasoning Tasks
Zhanke Zhou, Zongze Li, Weikai Huang +16
Agents pair reasoning models with harnesses that organize model calls, execute tools, load skill instructions, and retain history in memory. Understanding agent performance require…
What Do Evolutionary Coding Agents Evolve?
Nico Pelleriti, Sree Harsha Nelaturu, Zhanke Zhou +4
Recent work pairs LLMs with evolutionary search to iteratively generate, modify, and select code using task-specific feedback. These systems have produced strong results in mathema…
Reference-guided Policy Optimization for Molecular Optimization via LLM Reasoning
Xuan Li, Zhanke Zhou, Zongze Li +4
Large language models (LLMs) benefit substantially from supervised fine-tuning (SFT) and reinforcement learning with verifiable rewards (RLVR) in reasoning tasks. However, these re…
AlphaApollo: A System for Deep Agentic Reasoning
Zhanke Zhou, Chentao Cao, Xiao Feng +15
We present AlphaApollo, an agentic reasoning system that targets two bottlenecks in foundation-model reasoning: (1) limited reasoning capacity for complex, long-horizon problem sol…
The 1st International Workshop on Disentangled Representation Learning for Controllable Generation (DRL4Real): Methods and Results
Qiuyu Chen, Xin Jin, Yue Song +45
This paper reviews the 1st International Workshop on Disentangled Representation Learning for Controllable Generation (DRL4Real), held in conjunction with ICCV 2025. The workshop a…