6 papers
Reinforcement Learning for LLM-based Multi-Agent Systems through Orchestration Traces
Chenchen Zhang
As large language model (LLM) agents evolve from isolated tool users into coordinated teams, reinforcement learning (RL) must optimize not only individual actions but also how work…
WebCompass: Towards Multimodal Web Coding Evaluation for Code Language Models
Xinping Lei, Xinyu Che, Junqi Xiong +16
Large language models are rapidly evolving into interactive coding agents capable of end-to-end web coding, yet existing benchmarks evaluate only narrow slices of this capability,…
ReLook: Vision-Grounded RL with a Multimodal LLM Critic for Agentic Web Coding
Yuhang Li, Chenchen Zhang, Ruilin Lv +6
While Large Language Models (LLMs) excel at algorithmic code generation, they struggle with front-end development, where correctness is judged on rendered pixels and interaction. W…
ArtifactsBench: Bridging the Visual-Interactive Gap in LLM Code Generation Evaluation
Chenchen Zhang, Yuhang Li, Can Xu +17
The generative capabilities of Large Language Models (LLMs) are rapidly expanding from static code to dynamic, interactive visual artifacts. This progress is bottlenecked by a crit…
AutoCodeBench: Large Language Models are Automatic Code Benchmark Generators
Jason Chou, Ao Liu, Yuchi Deng +13
Large Language Models (LLMs) have demonstrated remarkable capabilities across various domains, with code generation emerging as a key area of focus. While numerous benchmarks have…
Multilingual Multimodal Software Developer for Code Generation
Linzheng Chai, Jian Yang, Shukai Liu +12
The rapid advancement of Large Language Models (LLMs) has significantly improved code generation, yet most models remain text-only, neglecting crucial visual aids like diagrams and…