5 papers · 1 filter
MolViBench: Evaluating LLMs on Molecular Vibe Coding
Jiatong Li, Yuxuan Ren, Weida Wang +4
Molecular Vibe Coding, a paradigm where chemists interact with LLMs to generate executable programs for molecular tasks, has emerged as a flexible alternative to chemical agents wi…
Mol-Debate: Multi-Agent Debate Improves Structural Reasoning in Molecular Design
Wengyu Zhang, Xiao-Yong Wei, Qing Li
Text-guided molecular design is a key capability for AI-driven drug discovery, yet it remains challenging to map sequential natural-language instructions with non-linear molecular…
Adaptive Multi-Agent Reasoning for Text-to-Video Retrieval
Jiaxin Wu, Xiao-Yong Wei, Qing Li
The rise of short-form video platforms and the emergence of multimodal large language models (MLLMs) have amplified the need for scalable, effective, zero-shot text-to-video retrie…
MarkovScale: Towards Optimal Sequential Scaling at Inference Time
Youkang Wang, Jian Wang, Rubing Chen +3
Sequential scaling is a prominent inference-time scaling paradigm, yet its performance improvements are typically modest and not well understood, largely due to the prevalence of h…
To Retrieve or To Think? Cross-Boundary Context Evolution for Multi-hop Complex Reasoning
Rubing Chen, Jian Wang, Wenjie Li +2
Current context augmentation methods, such as retrieval-augmented generation, play a crucial role in bridging a model's internal knowledge boundary and external evidence for multi-…