From the 1 of 11 linked papers with an AI index.
11 papers
MemOps: Benchmarking Lifecycle Memory Operations in Long-Horizon Conversations
Xixuan Hao, Zeyu Zhang, Zehao Lin +6
The paper introduces MemOps, a benchmark that evaluates long‑term conversational memory by tracking explicit lifecycle operations (remember, forget, update, etc.) rather than only…
Prompt and Parameter Co-Optimization for Large Language Models
Xiaohe Bo, Rui Li, Zexu Sun +5
Prompt optimization and fine-tuning are two major approaches to improve the performance of Large Language Models (LLMs). They enhance the capabilities of LLMs from complementary pe…
CAM: A Constructivist View of Agentic Memory for LLM-Based Reading Comprehension
Rui Li, Zeyu Zhang, Xiaohe Bo +5
Current Large Language Models (LLMs) are confronted with overwhelming information volume when comprehending long-form documents. This challenge raises the imperative of a cohesive…
Learn to Memorize: Optimizing LLM-based Agents with Adaptive Memory Framework
Zeyu Zhang, Quanyu Dai, Rui Li +3
LLM-based agents have been extensively applied across various domains, where memory stands out as one of their most essential capabilities. Previous memory mechanisms of LLM-based…
RecUserSim: A Realistic and Diverse User Simulator for Evaluating Conversational Recommender Systems
Luyu Chen, Quanyu Dai, Zeyu Zhang +6
Conversational recommender systems (CRS) enhance user experience through multi-turn interactions, yet evaluating CRS remains challenging. User simulators can provide comprehensive…
MemBench: Towards More Comprehensive Evaluation on the Memory of LLM-based Agents
Haoran Tan, Zeyu Zhang, Chen Ma +3
Recent works have highlighted the significance of memory mechanisms in LLM-based agents, which enable them to store observed information and adapt to dynamic environments. However,…