1 citations · 1 across the 2 of their papers we have counts for
13 papers
Learn-To-Learn on Arbitrary Textual Conditioning: A Hypernetwork-Driven Meta-Gated LLM
Luo Ji, Qi Qin, Ningyuan Xi +3
Conventional LLMs may suffer from corpus heterogeneity and subtle condition changes. While finetuning can create the catastrophe forgetting issue, application of meta-learning on L…
EmoFSM: A Finite State Machine for Emotional Support Conversation
Yue Zhao, Qingqing Gu, Xiaoyu Wang +5
Emotional support conversation (ESC) aims to alleviate people's emotional distress through effective conversations. Although large language models (LLMs) have made remarkable progr…
Efficient Rationale-based Retrieval: On-policy Distillation from Generative Rerankers based on JEPA
Teng Chen, Sheng Xu, Feixiang Guo +4
Unlike traditional fact-based retrieval, rationale-based retrieval typically necessitates cross-encoding of query-document pairs using large language models, incurring substantial…
From Descriptive to Prescriptive: Uncover the Social Value Alignment of LLM-based Agents
Jinxian Qu, Qingqing Gu, Teng Chen +1
Wide applications of LLM-based agents require strong alignment with human social values. However, current works still exhibit deficiencies in self-cognition and dilemma decision, a…
MeTHanol: Modularized Thinking Language Models with Intermediate Layer Thinking, Decoding and Bootstrapping Reasoning
Ningyuan Xi, Xiaoyu Wang, Yetao Wu +7
Current research efforts are focused on enhancing the thinking and reasoning capability of large language model (LLM) by prompting, data-driven emergence and inference-time computa…
Chain-of-Conceptual-Thought Elicits Daily Conversation in Large Language Models
Qingqing Gu, Dan Wang, Yue Zhao +5
Chain-of-Thought (CoT) is widely applied to enhance the LLM capability in math, coding and reasoning tasks. However, its performance is limited for open-domain tasks, when there ar…