activity
20192026
most citedEVA: An Open-Domain Chinese Dialogue System with Large-Scale Generative Pre-Training

29 citations · 83 across the 23 of their papers we have counts for

collaborators

33 papers

cs.CL2026

Breaking the Impasse: Dual-Scale Evolutionary Policy Training for Social Language Agents

Minzheng Wang, Run Luo, Yanbo Wang +6

While Reinforcement Learning with Verifiable Rewards (RLVR) has proven effective for closed-ended tasks, extending it to open-ended social language games via self-play reveals a cr…

cs.CL2024

Granular Change Accuracy: A More Accurate Performance Metric for Dialogue State Tracking

Taha Aksu, Nancy F. Chen

Current metrics for evaluating Dialogue State Tracking (DST) systems exhibit three primary limitations. They: i) erroneously presume a uniform distribution of slots throughout the…

cs.CL2023

PIPPA: A Partially Synthetic Conversational Dataset

Tear Gosling, Alpin Dale, Yinhe Zheng

With the emergence of increasingly powerful large language models, there is a burgeoning interest in leveraging these models for casual conversation and role-play applications. How…

cs.CL2023

Long-Tailed Question Answering in an Open World

Yi Dai, Hao Lang, Yinhe Zheng +2

Real-world data often have an open long-tailed distribution, and building a unified QA model supporting various tasks is vital for practical QA applications. However, it is non-tri…

cs.CL2023

Domain Incremental Lifelong Learning in an Open World

Yi Dai, Hao Lang, Yinhe Zheng +3

Lifelong learning (LL) is an important ability for NLP models to learn new tasks continuously. Architecture-based approaches are reported to be effective implementations for LL mod…

cs.CL2023★ 3 cited

Out-of-Domain Intent Detection Considering Multi-Turn Dialogue Contexts

Hao Lang, Yinhe Zheng, Binyuan Hui +2

Out-of-Domain (OOD) intent detection is vital for practical dialogue systems, and it usually requires considering multi-turn dialogue contexts. However, most previous OOD intent de…