3 citations · 3 across the 5 of their papers we have counts for
5 papers
T-Mem: Memory That Anticipates, Not Archives
Weidong Guo, Dakai Wang, Zixuan Wang +2
Long-term memory is essential for conversational agents to remain coherent across extended dialogues, follow through on commitments made many sessions earlier, and adapt their beha…
Locomo-Plus: Beyond-Factual Cognitive Memory Evaluation Framework for LLM Agents
Yifei Li, Weidong Guo, Lingling Zhang +6
Long-term conversational memory is a core capability for LLM-based dialogue systems, yet existing benchmarks and evaluation protocols primarily focus on surface-level factual recal…
TaCIE: Enhancing Instruction Comprehension in Large Language Models through Task-Centred Instruction Evolution
Jiuding Yang, Shengyao Lu, Weidong Guo +4
Large Language Models (LLMs) require precise alignment with complex instructions to optimize their performance in real-world applications. As the demand for refined instruction tun…
Enhancing and Assessing Instruction-Following with Fine-Grained Instruction Variants
Jiuding Yang, Weidong Guo, Kaitong Yang +3
The effective alignment of Large Language Models (LLMs) with precise instructions is essential for their application in diverse real-world scenarios. Current methods focus on enhan…
HRLAIF: Improvements in Helpfulness and Harmlessness in Open-domain Reinforcement Learning From AI Feedback
Ang Li, Qiugen Xiao, Peng Cao +12
Reinforcement Learning from AI Feedback (RLAIF) has the advantages of shorter annotation cycles and lower costs over Reinforcement Learning from Human Feedback (RLHF), making it hi…