4 papers
LLM4RTL: Tool-Assisted LLM for RTL Generation
Jing Jin, Robert Chu, Ning Yan +1
Large language models (LLMs) have facilitated impressive progress in software engineering, code generation, tooling, and systems. Concurrently, a significant body of research has d…
ExpThink: Experience-Guided Reinforcement Learning for Adaptive Chain-of-Thought Compression
Tingcheng Bian, Yuzhe Zhang, Jing Jin +5
Large reasoning models (LRMs) achieve strong performance via extended chain-of-thought (CoT) reasoning, yet suffer from excessive token consumption and high inference latency. Exis…
Unveiling Fine-Grained Visual Traces: Evaluating Multimodal Interleaved Reasoning Chains in Multimodal STEM Tasks
Jing Jin, Hao Liu, Yan Bai +9
Multimodal large language models (MLLMs) have shown promising reasoning abilities, yet evaluating their performance in specialized domains remains challenging. STEM reasoning is a…
InstructPipe: Generating Visual Blocks Pipelines with Human Instructions and LLMs
Zhongyi Zhou, Jing Jin, Vrushank Phadnis +16
Visual programming has the potential of providing novice programmers with a low-code experience to build customized processing pipelines. Existing systems typically require users t…