16 citations · 24 across the 8 of their papers we have counts for
10 papers
FORGE: Fine-grained Multimodal Evaluation for Manufacturing Scenarios
Xiangru Jian, Hao Xu, Wei Pang +13
The manufacturing sector is increasingly adopting Multimodal Large Language Models (MLLMs) to transition from simple perception to autonomous execution, yet current evaluations fai…
Effective Policy Learning for Multi-Agent Online Coordination Beyond Submodular Objectives
Qixin Zhang, Yan Sun, Can Jin +5
In this paper, we present two effective policy learning algorithms for multi-agent online coordination(MA-OC) problem. The first one, \texttt{MA-SPL}, not only can achieve the opti…
MMReason: An Open-Ended Multi-Modal Multi-Step Reasoning Benchmark for MLLMs Toward AGI
Huanjin Yao, Jiaxing Huang, Yawen Qiu +9
Reasoning plays a crucial role in advancing Multimodal Large Language Models (MLLMs) toward Artificial General Intelligence. However, existing MLLM benchmarks often fall short in p…
Improving Large Language Models with Concept-Aware Fine-Tuning
Michael K. Chen, Xikun Zhang, Jiaxing Huang +1
Large language models (LLMs) have become the cornerstone of modern AI. However, the existing paradigm of next-token prediction fundamentally limits their ability to form coherent,…
A Survey of Direct Preference Optimization
Shunyu Liu, Wenkai Fang, Zetian Hu +9
Large Language Models (LLMs) have demonstrated unprecedented generative capabilities, yet their alignment with human values remains critical for ensuring helpful and harmless deplo…
R1-VL: Learning to Reason with Multimodal Large Language Models via Step-wise Group Relative Policy Optimization
Jingyi Zhang, Jiaxing Huang, Huanjin Yao +4
Recent studies generally enhance MLLMs' reasoning capabilities via supervised fine-tuning on high-quality chain-of-thought reasoning data, which often leads models to merely imitat…
JustLogic: A Comprehensive Benchmark for Evaluating Deductive Reasoning in Large Language Models
Michael K. Chen, Xikun Zhang, Dacheng Tao
Logical reasoning is a critical component of Large Language Models (LLMs), and substantial research efforts in recent years have aimed to enhance their deductive reasoning capabili…
Learning System Dynamics without Forgetting
Xikun Zhang, Dongjin Song, Yushan Jiang +2
Observation-based trajectory prediction for systems with unknown dynamics is essential in fields such as physics and biology. Most existing approaches are limited to learning withi…
Continual Learning on Graphs: Challenges, Solutions, and Opportunities
Xikun Zhang, Dongjin Song, Dacheng Tao
Continual learning on graph data has recently attracted paramount attention for its aim to resolve the catastrophic forgetting problem on existing tasks while adapting the sequenti…
Topology-aware Embedding Memory for Continual Learning on Expanding Networks
Xikun Zhang, Dongjin Song, Yixin Chen +1
Memory replay based techniques have shown great success for continual learning with incrementally accumulated Euclidean data. Directly applying them to continually expanding networ…