Chen Zhang's repositories
dstc10_metric_track
The Official Repository for the Automatic Dialogue Evaluation Sub-task of DSTC10 Track 5 (Automatic Evaluation and Moderation of Open-domain Dialogue Systems)
FineD-Eval
Repository for EMNLP-2022 Paper (FineD-Eval: Fine-grained Automatic Dialogue-Level Evaluation)
xDial-Eval
Repository for EMNLP-2023 Findings Paper - xDial-Eval: A Multilingual Open-Domain Dialogue Evaluation Benchmark
comp-analysis
Repository for AAAI-2024 Paper - A Comprehensive Analysis of the Effectiveness of Large Language Models as Automatic Dialogue Evaluators
aiXcoder-7B
official repository of aiXcoder-7B Code Large Language Model
alexa-with-dstc10-track2-dataset
DSTC10 Track 2 - Knowledge-grounded Task-oriented Dialogue Modeling on Spoken Conversations
BARTScore
BARTScore: Evaluating Generated Text as Text Generation
bigbird
Transformers for Longer Sequences
google-research
Google Research
human-eval
Code for the paper "Evaluating Large Language Models Trained on Code"
lm-evaluation-harness
A framework for few-shot evaluation of autoregressive language models.
mixture-of-experts
PyTorch Re-Implementation of "The Sparsely-Gated Mixture-of-Experts Layer" by Noam Shazeer et al. https://arxiv.org/abs/1701.06538
online_dialog_eval
Code for the paper "Learning an Unreferenced Metric for Online Dialogue Evaluation", ACL 2020
perfect
PERFECT: Prompt-free and Efficient Few-shot Learning with Language Models
personal-website
Code that'll help you kickstart a personal website that showcases your work as a software developer.
PLMTuningCompetition
擂台赛3-大规模预训练调优比赛的示例代码与baseline实现
SPIN
The official implementation of Self-Play Fine-Tuning (SPIN)
t5-dst-modified-pytorch
Modified version of T5-DST for Dialogue State Tracking.
Top-AI-Conferences-Paper-with-Code
Top-Conferences-Paper-with-Code (ACL、EMNLP、NAACL、COLING、AAAI、IJCAI、NeurIPS、ICLR and etc)
Top-conference-paper-list
A collection of classified and organized top conference paper list.
trade-dst
Source code for transferable dialogue state generator (TRADE, Wu et al., 2019). https://arxiv.org/abs/1905.08743
transformers
🤗Transformers: State-of-the-art Natural Language Processing for Pytorch and TensorFlow 2.0.