collaborators

9 papers

cs.CV2026

CoCoSI: Collaborative Cognitive Map Construction for Spatial Intelligence

Yiming Zhang, Ruoxuan Cao, Zhihang Zhong

Spatial intelligence is a key frontier for multimodal large language models (MLLMs), enabling them to reason about the physical world from visual experience. Inspired by human spat…

cs.CL2026

SkillBrew: Multi-Objective Curation of Skill Banks for LLM Agents

Wentao Hu, Zhendong Chu, Yiming Zhang +6

Retrieval-augmented LLM agents increasingly rely on curated skill banks: collections of reusable textual principles that guide decision making on complex tasks. Existing approaches…

cs.AI2026

ProvMind: Provenance-grounded reasoning for materials synthesis

Yiming Zhang, Ryo Tamura, Koji Tsuda

Materials process optimization requires reasoning over routes, conditions, tools and causal dependencies, yet most computational formulations flatten synthesis procedures into text…

cs.LG2026

InfiFPO: Implicit Model Fusion via Preference Optimization in Large Language Models

Yanggan Gu, Yuanyi Wang, Zhaoyi Yan +4

Model fusion combines multiple Large Language Models (LLMs) with different strengths into a more powerful, integrated model through lightweight training methods. Existing works on…

cs.CL2026

InfiGFusion: Graph-on-Logits Distillation via Efficient Gromov-Wasserstein for Model Fusion

Yuanyi Wang, Zhaoyi Yan, Yiming Zhang +4

Recent advances in large language models (LLMs) have intensified efforts to fuse heterogeneous open-source models into a unified system that inherits their complementary strengths.…

cs.AI2026

Model Merging Scaling Laws in Large Language Models

Yuanyi Wang, Yanggan Gu, Yiming Zhang +6

We study empirical scaling laws for language model merging measured by cross-entropy. Despite its wide practical use, merging lacks a quantitative rule that predicts returns as we…