20 citations · 40 across the 12 of their papers we have counts for
12 papers
Topic-driven Distant Supervision Framework for Macro-level Discourse Parsing
Feng Jiang, Longwang He, Peifeng Li +2
Discourse parsing, the task of analyzing the internal rhetorical structure of texts, is a challenging problem in natural language processing. Despite the recent advances in neural…
Dynamic Transformers Provide a False Sense of Efficiency
Yiming Chen, Simin Chen, Zexin Li +4
Despite much success in natural language processing (NLP), pre-trained language models typically lead to a high computational cost during inference. Multi-exit is a mainstream appr…
Enhancing Black-Box Few-Shot Text Classification with Prompt-Based Data Augmentation
Danqing Luo, Chen Zhang, Jiahui Xu +4
Training or finetuning large-scale language models (LLMs) such as GPT-3 requires substantial computation resources, motivating recent efforts to explore parameter-efficient adaptat…
Phoenix: Democratizing ChatGPT across Languages
Zhihong Chen, Feng Jiang, Junying Chen +11
This paper presents our efforts to democratize ChatGPT across language. We release a large language model "Phoenix", achieving competitive performance among open-source English and…
PoE: a Panel of Experts for Generalized Automatic Dialogue Assessment
Chen Zhang, Luis Fernando D'Haro, Qiquan Zhang +2
Chatbots are expected to be knowledgeable across multiple domains, e.g. for daily chit-chat, exchange of information, and grounding in emotional situations. To effectively measure…
Relational Sentence Embedding for Flexible Semantic Matching
Bin Wang, Haizhou Li
We present Relational Sentence Embedding (RSE), a new paradigm to further discover the potential of sentence embeddings. Prior work mainly models the similarity between sentences b…
FineD-Eval: Fine-grained Automatic Dialogue-Level Evaluation
Chen Zhang, Luis Fernando D'Haro, Qiquan Zhang +2
Recent model-based reference-free metrics for open-domain dialogue evaluation exhibit promising correlations with human judgment. However, they either perform turn-level evaluation…
A Focused Study on Sequence Length for Dialogue Summarization
Bin Wang, Chen Zhang, Chengwei Wei +1
Output length is critical to dialogue summarization systems. The dialogue summary length is determined by multiple factors, including dialogue complexity, summary objective, and pe…
Analyzing and Evaluating Faithfulness in Dialogue Summarization
Bin Wang, Chen Zhang, Yan Zhang +2
Dialogue summarization is abstractive in nature, making it suffer from factual errors. The factual correctness of summaries has the highest priority before practical applications.…
Just Rank: Rethinking Evaluation with Word and Sentence Similarities
Bin Wang, C. -C. Jay Kuo, Haizhou Li
Word and sentence embeddings are useful feature representations in natural language processing. However, intrinsic evaluation for embeddings lags far behind, and there has been no…
MDD-Eval: Self-Training on Augmented Data for Multi-Domain Dialogue Evaluation
Chen Zhang, Luis Fernando D'Haro, Thomas Friedrichs +1
Chatbots are designed to carry out human-like conversations across different domains, such as general chit-chat, knowledge exchange, and persona-grounded conversations. To measure…
Investigating the Impact of Pre-trained Language Models on Dialog Evaluation
Chen Zhang, Luis Fernando D'Haro, Yiming Chen +2
Recently, there is a surge of interest in applying pre-trained language models (Pr-LM) in automatic open-domain dialog evaluation. Pr-LMs offer a promising direction for addressing…