27 citations · 82 across the 15 of their papers we have counts for
17 papers
SWEPatchTest: Evaluating Software Tests Beyond Reproduction
Hua Lu, Pengcheng Wang, Han Li +4
Coding agents use generated tests to decide whether a proposed patch satisfies an issue's requirements. A suite that fails on the buggy program and passes after applying the refere…
Distributional Clarity: The Hidden Driver of RL-Friendliness in Large Language Models
Shaoning Sun, Mingzhu Cai, Huang He +5
Language model families exhibit striking disparity in their capacity to benefit from reinforcement learning: under identical training, models like Qwen achieve substantial gains, w…
ProxyAttn: Guided Sparse Attention via Representative Heads
Yixuan Wang, Huang He, Siqi Bao +4
The quadratic complexity of attention mechanisms limits the efficiency of Large Language Models (LLMs) on long-text tasks. Recently, methods that dynamically estimate block importa…
Query Enhanced Knowledge-Intensive Conversation via Unsupervised Joint Modeling
Mingzhu Cai, Siqi Bao, Xin Tian +3
In this paper, we propose an unsupervised query enhanced approach for knowledge-intensive conversations, namely QKConv. There are three modules in QKConv: a query generator, an off…
PLATO-K: Internal and External Knowledge Enhanced Dialogue Generation
Siqi Bao, Huang He, Jun Xu +7
Recently, the practical deployment of open-domain dialogue systems has been plagued by the knowledge issue of information deficiency and factual inaccuracy. To this end, we introdu…
Q-TOD: A Query-driven Task-oriented Dialogue System
Xin Tian, Yingzhan Lin, Mengfei Song +5
Existing pipelined task-oriented dialogue systems usually have difficulties adapting to unseen domains, whereas end-to-end systems are plagued by large-scale knowledge bases in pra…
Towards Boosting the Open-Domain Chatbot with Human Feedback
Hua Lu, Siqi Bao, Huang He +3
Many open-domain dialogue models pre-trained with social media comments can generate coherent replies but have difficulties producing engaging responses when interacting with real…
Towards Building an Open-Domain Dialogue System Incorporated with Internet Memes
Hua Lu, Zhen Guo, Chanjuan Li +3
In recent years, Internet memes have been widely used in online chatting. Compared with text-based communication, conversations become more expressive and attractive when Internet…
TOD-DA: Towards Boosting the Robustness of Task-oriented Dialogue Modeling on Spoken Conversations
Xin Tian, Xinxian Huang, Dongfeng He +11
Task-oriented dialogue systems have been plagued by the difficulties of obtaining large-scale and high-quality annotated conversations. Furthermore, most of the publicly available…
Amendable Generation for Dialogue State Tracking
Xin Tian, Liankai Huang, Yingzhan Lin +6
In task-oriented dialogue systems, recent dialogue state tracking methods tend to perform one-pass generation of the dialogue state based on the previous dialogue state. The mistak…
PLATO-XL: Exploring the Large-scale Pre-training of Dialogue Generation
Siqi Bao, Huang He, Fan Wang +11
To explore the limit of dialogue generation pre-training, we present the models of PLATO-XL with up to 11 billion parameters, trained on both Chinese and English social media conve…
A Unified Pre-training Framework for Conversational AI
Siqi Bao, Bingjin Chen, Huang He +7
In this work, we explore the application of PLATO-2 on various dialogue systems, including open-domain conversation, knowledge grounded dialogue, and task-oriented conversation. PL…
Learning to Select External Knowledge with Multi-Scale Negative Sampling
Huang He, Hua Lu, Siqi Bao +4
The Track-1 of DSTC9 aims to effectively answer user requests or questions during task-oriented dialogues, which are out of the scope of APIs/DB. By leveraging external knowledge r…
PLATO-2: Towards Building an Open-Domain Chatbot via Curriculum Learning
Siqi Bao, Huang He, Fan Wang +6
To build a high-quality open-domain chatbot, we introduce the effective training process of PLATO-2 via curriculum learning. There are two stages involved in the learning process.…
PLATO: Pre-trained Dialogue Generation Model with Discrete Latent Variable
Siqi Bao, Huang He, Fan Wang +2
Pre-training models have been proved effective for a wide range of natural language processing tasks. Inspired by this, we propose a novel dialogue generation pre-training framewor…
Know More about Each Other: Evolving Dialogue Strategy via Compound Assessment
Siqi Bao, Huang He, Fan Wang +2
In this paper, a novel Generation-Evaluation framework is developed for multi-turn conversations with the objective of letting both participants know more about each other. For the…
Familia: A Configurable Topic Modeling Framework for Industrial Text Engineering
Di Jiang, Yuanfeng Song, Rongzhong Lian +4
In the last decade, a variety of topic models have been proposed for text engineering. However, except Probabilistic Latent Semantic Analysis (PLSA) and Latent Dirichlet Allocation…