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MemoryRewardBench: Benchmarking Reward Models for Long-Term Memory Management in Large Language Models

Beginner

Zecheng Tang, Baibei Ji et al.Jan 17arXiv

This paper builds MemoryRewardBench, a big test that checks if reward models (AI judges) can fairly grade how other AIs manage long-term memory, not just whether their final answers are right.

#reward models#long-term memory#long-context reasoning

RealMem: Benchmarking LLMs in Real-World Memory-Driven Interaction

Beginner

Haonan Bian, Zhiyuan Yao et al.Jan 11arXiv

RealMem is a new benchmark that tests how well AI assistants remember and manage long, ongoing projects across many conversations.

#RealMem#long-term memory#project-oriented interactions

Confucius Code Agent: Scalable Agent Scaffolding for Real-World Codebases

Beginner

Sherman Wong, Zhenting Qi et al.Dec 11arXiv

This paper introduces the Confucius Code Agent (CCA), a coding helper built to handle huge real-world codebases with long tasks and many tools.

#coding agents#agent scaffolding#context management

Papers3

MemoryRewardBench: Benchmarking Reward Models for Long-Term Memory Management in Large Language Models

RealMem: Benchmarking LLMs in Real-World Memory-Driven Interaction

Confucius Code Agent: Scalable Agent Scaffolding for Real-World Codebases