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20202026
most citedDDRel: A New Dataset for Interpersonal Relation Classification in Dyadic Dialogues

2 citations · 4 across the 4 of their papers we have counts for

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Showing cs.CLShow all

6 papers · 1 filter

cs.CL2023

Context Compression for Auto-regressive Transformers with Sentinel Tokens

Siyu Ren, Qi Jia, Kenny Q. Zhu

The quadratic complexity of the attention module makes it gradually become the bulk of compute in Transformer-based LLMs during generation. Moreover, the excessive key-value cache…

cs.CL2023

Zero-shot Faithfulness Evaluation for Text Summarization with Foundation Language Model

Qi Jia, Siyu Ren, Yizhu Liu +1

Despite tremendous improvements in natural language generation, summarization models still suffer from the unfaithfulness issue. Previous work evaluates faithfulness either using m…

cs.CL2023

Reducing Sensitivity on Speaker Names for Text Generation from Dialogues

Qi Jia, Haifeng Tang, Kenny Q. Zhu

Changing speaker names consistently throughout a dialogue should not affect its meaning and corresponding outputs for text generation from dialogues. However, pre-trained language…

cs.CL20222 cited

Post-Training Dialogue Summarization using Pseudo-Paraphrasing

Qi Jia, Yizhu Liu, Haifeng Tang +1

Previous dialogue summarization techniques adapt large language models pretrained on the narrative text by injecting dialogue-specific features into the models. These features eith…

cs.CL20202 cited

DDRel: A New Dataset for Interpersonal Relation Classification in Dyadic Dialogues

Qi Jia, Hongru Huang, Kenny Q. Zhu

Interpersonal language style shifting in dialogues is an interesting and almost instinctive ability of human. Understanding interpersonal relationship from language content is also…

cs.CL2020

Matching Questions and Answers in Dialogues from Online Forums

Qi Jia, Mengxue Zhang, Shengyao Zhang +1

Matching question-answer relations between two turns in conversations is not only the first step in analyzing dialogue structures, but also valuable for training dialogue systems.…