1 citations · 1 across the 10 of their papers we have counts for
11 papers
GLaQ: Grounding Latent Queries in Visual Evidence for Multimodal Reasoning
Zesheng Yang, Lingling Zhang, Xinyu Zhang +4
Chain-of-thought reasoning has substantially improved the problem-solving capabilities of multimodal large language models. Fine-grained visual evidence, however, remains difficult…
QUMem: Personalized Memory for Query-Conditioned User-State Inference in LLM Agents
Heng Wang, Yifei Li, Lingling Zhang +4
Large language model (LLM) agents increasingly use external memory systems to support personalization by drawing on long and evolving interaction histories, in which user preferenc…
Beyond Retrieval: Query-Conditioned Reuse of Long-Horizon Agent Trajectories
Yifei Li, Heng Wang, Lingling Zhang +5
Retrieval can identify a past trajectory that may matter, yet it does not specify how an acting agent should use that trajectory after users, entities, constraints, or environment…
Dual-Cluster Memory Agent: Resolving Multi-Paradigm Ambiguity in Optimization Problem Solving
Xinyu Zhang, Yuchen Wan, Boxuan Zhang +4
Large Language Models (LLMs) often struggle with structural ambiguity in optimization problems, where a single problem admits multiple related but conflicting modeling paradigms, h…
OptiVerse: A Comprehensive Benchmark towards Optimization Problem Solving
Xinyu Zhang, Boxuan Zhang, Yuchen Wan +5
While Large Language Models (LLMs) demonstrate remarkable reasoning, complex optimization tasks remain challenging, requiring domain knowledge and robust implementation. However, e…
LogicGraph : Benchmarking Multi-Path Logical Reasoning via Neuro-Symbolic Generation and Verification
Yanrui Wu, Lingling Zhang, Xinyu Zhang +5
Evaluations of large language models (LLMs) primarily emphasize convergent logical reasoning, where success is defined by producing a single correct proof. However, many real-world…
CoFFT: Chain of Foresight-Focus Thought for Visual Language Models
Xinyu Zhang, Yuxuan Dong, Lingling Zhang +5
Despite significant advances in Vision Language Models (VLMs), they remain constrained by the complexity and redundancy of visual input. When images contain large amounts of irrele…
PhysReason: A Comprehensive Benchmark towards Physics-Based Reasoning
Xinyu Zhang, Yuxuan Dong, Yanrui Wu +6
Large language models demonstrate remarkable capabilities across various domains, especially mathematics and logic reasoning. However, current evaluations overlook physics-based re…
Diagram-Driven Course Questions Generation
Xinyu Zhang, Lingling Zhang, Yanrui Wu +6
Visual Question Generation (VQG) research focuses predominantly on natural images while neglecting the diagram, which is a critical component in educational materials. To meet the…
VProChart: Answering Chart Question through Visual Perception Alignment Agent and Programmatic Solution Reasoning
Muye Huang, Lingling Zhang, Lai Han +3
Charts are widely used for data visualization across various fields, including education, research, and business. Chart Question Answering (CQA) is an emerging task focused on the…
EvoChart: A Benchmark and a Self-Training Approach Towards Real-World Chart Understanding
Muye Huang, Han Lai, Xinyu Zhang +4
Chart understanding enables automated data analysis for humans, which requires models to achieve highly accurate visual comprehension. While existing Visual Language Models (VLMs)…