7 citations · 19 across the 18 of their papers we have counts for
18 papers
NC-NCD: Novel Class Discovery for Node Classification
Yue Hou, Xueyuan Chen, He Zhu +5
Novel Class Discovery (NCD) involves identifying new categories within unlabeled data by utilizing knowledge acquired from previously established categories. However, existing NCD…
UniCoder: Scaling Code Large Language Model via Universal Code
Tao Sun, Linzheng Chai, Jian Yang +6
Intermediate reasoning or acting steps have successfully improved large language models (LLMs) for handling various downstream natural language processing (NLP) tasks. When applyin…
GIEBench: Towards Holistic Evaluation of Group Identity-based Empathy for Large Language Models
Leyan Wang, Yonggang Jin, Tianhao Shen +9
As large language models (LLMs) continue to develop and gain widespread application, the ability of LLMs to exhibit empathy towards diverse group identities and understand their pe…
Iterative Length-Regularized Direct Preference Optimization: A Case Study on Improving 7B Language Models to GPT-4 Level
Jie Liu, Zhanhui Zhou, Jiaheng Liu +4
Direct Preference Optimization (DPO), a standard method for aligning language models with human preferences, is traditionally applied to offline preferences. Recent studies show th…
McEval: Massively Multilingual Code Evaluation
Linzheng Chai, Shukai Liu, Jian Yang +15
Code large language models (LLMs) have shown remarkable advances in code understanding, completion, and generation tasks. Programming benchmarks, comprised of a selection of code c…
Towards Real-world Scenario: Imbalanced New Intent Discovery
Shun Zhang, Chaoran Yan, Jian Yang +5
New Intent Discovery (NID) aims at detecting known and previously undefined categories of user intent by utilizing limited labeled and massive unlabeled data. Most prior works ofte…