6 citations · 20 across the 10 of their papers we have counts for
11 papers
Unleashing Implicit Rewards: Prefix-Value Learning for Distribution-Level Optimization
Shiping Gao, Hongzhan Chen, Xiaojun Quan +2
Process reward models (PRMs) provide fine-grained supervision for reasoning, but reliable PRMs often require step annotations or heavy verification pipelines, making them costly to…
Probabilistic Token Alignment for Large Language Model Fusion
Runjia Zeng, James Chenhao Liang, Cheng Han +8
Training large language models (LLMs) from scratch can yield models with unique functionalities and strengths, but it is costly and often leads to redundant capabilities. A more co…
Advantage-Guided Distillation for Preference Alignment in Small Language Models
Shiping Gao, Fanqi Wan, Jiajian Guo +2
Alignment techniques enable Large Language Models (LLMs) to generate outputs that align with human preferences and play a crucial role in their effectiveness. However, their impact…
PsyPlay: Personality-Infused Role-Playing Conversational Agents
Tao Yang, Yuhua Zhu, Xiaojun Quan +2
The current research on Role-Playing Conversational Agents (RPCAs) with Large Language Models (LLMs) primarily focuses on imitating specific speaking styles and utilizing character…
PsyCoT: Psychological Questionnaire as Powerful Chain-of-Thought for Personality Detection
Tao Yang, Tianyuan Shi, Fanqi Wan +4
Recent advances in large language models (LLMs), such as ChatGPT, have showcased remarkable zero-shot performance across various NLP tasks. However, the potential of LLMs in person…
Dual-Feedback Knowledge Retrieval for Task-Oriented Dialogue Systems
Tianyuan Shi, Liangzhi Li, Zijian Lin +3
Efficient knowledge retrieval plays a pivotal role in ensuring the success of end-to-end task-oriented dialogue systems by facilitating the selection of relevant information necess…
Disentangled Phonetic Representation for Chinese Spelling Correction
Zihong Liang, Xiaojun Quan, Qifan Wang
Chinese Spelling Correction (CSC) aims to detect and correct erroneous characters in Chinese texts. Although efforts have been made to introduce phonetic information (Hanyu Pinyin)…
AD-KD: Attribution-Driven Knowledge Distillation for Language Model Compression
Siyue Wu, Hongzhan Chen, Xiaojun Quan +2
Knowledge distillation has attracted a great deal of interest recently to compress pre-trained language models. However, existing knowledge distillation methods suffer from two lim…
Orders Are Unwanted: Dynamic Deep Graph Convolutional Network for Personality Detection
Tao Yang, Jinghao Deng, Xiaojun Quan +1
Predicting personality traits based on online posts has emerged as an important task in many fields such as social network analysis. One of the challenges of this task is assemblin…
AD-DROP: Attribution-Driven Dropout for Robust Language Model Fine-Tuning
Tao Yang, Jinghao Deng, Xiaojun Quan +2
Fine-tuning large pre-trained language models on downstream tasks is apt to suffer from overfitting when limited training data is available. While dropout proves to be an effective…
Autoregressive Entity Generation for End-to-End Task-Oriented Dialog
Guanhuan Huang, Xiaojun Quan, Qifan Wang
Task-oriented dialog (TOD) systems often require interaction with an external knowledge base to retrieve necessary entity (e.g., restaurant) information to support the response gen…