6 citations · 7 across the 6 of their papers we have counts for
5 papers · 1 filter
When Errors Become Memories: Causal Pathway Tracing in Multi-Turn Memory-Augmented LLMs
Shuyao Xiao, Shengling Wang, Xuan Chen +8
Long-term memory enables large language models (LLMs) to preserve and reuse information across interactions, but it can also turn localized errors into persistent risks. Existing w…
ASTRA: Automated Synthesis of agentic Trajectories and Reinforcement Arenas
Xiaoyu Tian, Haotian Wang, Shuaiting Chen +12
Large language models (LLMs) are increasingly used as tool-augmented agents for multi-step decision making, yet training robust tool-using agents remains challenging. Existing meth…
Dial-insight: Fine-tuning Large Language Models with High-Quality Domain-Specific Data Preventing Capability Collapse
Jianwei Sun, Chaoyang Mei, Linlin Wei +4
The efficacy of large language models (LLMs) is heavily dependent on the quality of the underlying data, particularly within specialized domains. A common challenge when fine-tunin…
From LLM to Conversational Agent: A Memory Enhanced Architecture with Fine-Tuning of Large Language Models
Na Liu, Liangyu Chen, Xiaoyu Tian +3
This paper introduces RAISE (Reasoning and Acting through Scratchpad and Examples), an advanced architecture enhancing the integration of Large Language Models (LLMs) like GPT-4 in…
DUMA: a Dual-Mind Conversational Agent with Fast and Slow Thinking
Xiaoyu Tian, Liangyu Chen, Na Liu +4
Inspired by the dual-process theory of human cognition, we introduce DUMA, a novel conversational agent framework that embodies a dual-mind mechanism through the utilization of two…