28 citations · 81 across the 35 of their papers we have counts for
7 papers · 1 filter
Mem-Gallery: Benchmarking Multimodal Long-Term Conversational Memory for MLLM Agents
Yuanchen Bei, Tianxin Wei, Xuying Ning +7
Long-term memory is a critical capability for multimodal large language model (MLLM) agents, particularly in conversational settings where information accumulates and evolves over…
Efficient and Transferable Agentic Knowledge Graph RAG via Reinforcement Learning
Junhong Lin, Shicheng Liu, Jinyeop Song +3
Knowledge-graph retrieval-augmented generation (KG-RAG) couples large language models (LLMs) with structured, verifiable knowledge graphs (KGs) to reduce hallucination and provide…
RAG over Tables: Hierarchical Memory Index, Multi-Stage Retrieval, and Benchmarking
Jiaru Zou, Dongqi Fu, Sirui Chen +5
Retrieval-Augmented Generation (RAG) enhances Large Language Models (LLMs) by integrating them with an external knowledge base to improve the answer relevance and accuracy. In real…
PLAY2PROMPT: Zero-shot Tool Instruction Optimization for LLM Agents via Tool Play
Wei Fang, Yang Zhang, Kaizhi Qian +2
Large language models (LLMs) are increasingly integrated with specialized external tools, yet many tasks demand zero-shot tool usage with minimal or noisy documentation. Existing s…
Enterprise Benchmarks for Large Language Model Evaluation
Bing Zhang, Mikio Takeuchi, Ryo Kawahara +5
The advancement of large language models (LLMs) has led to a greater challenge of having a rigorous and systematic evaluation of complex tasks performed, especially in enterprise a…
Self-Specialization: Uncovering Latent Expertise within Large Language Models
Junmo Kang, Hongyin Luo, Yada Zhu +6
Recent works have demonstrated the effectiveness of self-alignment in which a large language model is aligned to follow general instructions using instructional data generated from…
On Sample Based Explanation Methods for NLP:Efficiency, Faithfulness, and Semantic Evaluation
Wei Zhang, Ziming Huang, Yada Zhu +3
In the recent advances of natural language processing, the scale of the state-of-the-art models and datasets is usually extensive, which challenges the application of sample-based…