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Preference-Aware Memory Update for Long-Term LLM Agents
Haoran Sun, Zekun Zhang, Shaoning Zeng
One of the key factors influencing the reasoning capabilities of LLM-based agents is their ability to leverage long-term memory. Integrating long-term memory mechanisms allows agen…
Think Parallax: Solving Multi-Hop Problems via Multi-View Knowledge-Graph-Based Retrieval-Augmented Generation
Jinliang Liu, Jiale Bai, Shaoning Zeng
Large language models (LLMs) still struggle with multi-hop reasoning over knowledge-graphs (KGs), and we identify a previously overlooked structural reason for this difficulty: Tra…
Hierarchical Memory for High-Efficiency Long-Term Reasoning in LLM Agents
Haoran Sun, Shaoning Zeng
Long-term memory is one of the key factors influencing the reasoning capabilities of Large Language Model Agents (LLM Agents). Incorporating a memory mechanism that effectively int…
A Novel Self-Evolution Framework for Large Language Models
Haoran Sun, Zekun Zhang, Shaoning Zeng
The capabilities of Large Language Models (LLMs) are limited to some extent by pre-training, so some researchers optimize LLMs through post-training. Existing post-training strateg…