6 citations · 6 across the 7 of their papers we have counts for
9 papers
Harness-Search: Guiding Long-Horizon Search through Multi-Agent Coordination
Shanyong Wang, Zhenwen Ji, Lei Jin +7
Long-horizon search requires agents to gather evidence across multiple steps and synthesize it into well-supported answers. The recent agent harnesses provide a natural and promisi…
Momentum-Coupled Rubric Adaptation for Detailed Image Captioning
Zhenwen Ji, Lei Jin, Shanyong Wang +6
Detailed image captioning requires accurate and comprehensive descriptions of fine-grained visual content, yet caption quality spans factual accuracy, information coverage, and cla…
MemLens: A Value-Aware Memory Management System with Interactive Analytics for LLM-based Agents
Shuyue Wei, Chang Liu, Zimu Zhou +2
Recently, memory management has become a key infrastructure for LLM-based agents, as it directly affects long-horizon reasoning, personalized responses, and knowledge reuse. Howeve…
GraphDx: A Cost-Aware Knowledge-Enhanced Multi-Agent Framework for Sequential Diagnosis
Shaoting Tan, Ning Liu, Yuntao Du +7
Sequential diagnosis requires balancing diagnostic accuracy against resource costs through iterative information gathering. Existing Large Language Model (LLM) approaches exhibit a…
Delineating Knowledge Boundaries for Honest Large Vision-Language Models
Junru Song, Yimeng Hu, Yijing Chen +4
Large Vision-Language Models (VLMs) have achieved remarkable multimodal performance yet remain prone to factual hallucinations, particularly in long-tail or specialized domains. Mo…
M3MAD-Bench: Multi-Dimensional Evaluation of Multi-Agent Debate Across Domains and Modalities
Ao Li, Jinghui Zhang, Luyu Li +10
As an agent-level reasoning and coordination paradigm, Multi-Agent Debate (MAD) orchestrates multiple agents through structured debate to improve answer quality and support complex…
Can Visual Input Be Compressed? A Visual Token Compression Benchmark for Large Multimodal Models
Tianfan Peng, Yuntao Du, Pengzhou Ji +9
Large multimodal models (LMMs) often suffer from severe inference inefficiency due to the large number of visual tokens introduced by image encoders. While recent token compression…
Benchmarking Multimodal Knowledge Conflict for Large Multimodal Models
Yifan Jia, Kailin Jiang, Yuyang Liang +11
Large Multimodal Models(LMMs) face notable challenges when encountering multimodal knowledge conflicts, particularly under retrieval-augmented generation(RAG) frameworks where the…
Large Language Model Enhanced Text-to-SQL Generation: A Survey
Xiaohu Zhu, Qian Li, Lizhen Cui +1
Text-to-SQL translates natural language queries into Structured Query Language (SQL) commands, enabling users to interact with databases using natural language. Essentially, the te…