Papers by Byeongchang Kim
Will I Sound Like Me? Improving Persona Consistency in Dialogues through Pragmatic Self-Consciousness (2020.emnlp-main)
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| Challenge: | Existing models for improving consistency often train with additional NLI labels or attach trained extra modules to the generative agent. |
| Approach: | They propose to encode personas into dialogue embeddings and a persona-conditioned dialogue dataset to improve persona consistency. |
| Outcome: | The proposed approach can enforce dialogue agents to refrain from contradictions and improve consistency of existing models. |
Abstractive Summarization of Reddit Posts with Multi-level Memory Networks (N19-1)
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| Challenge: | Abstractive summarization methods suffer from inferior performance compared to extractive methods. |
| Approach: | They propose a reddit TIFU dataset and a new abstractive summarization model . they use multi-level memory networks to store information from different levels of abstraction . |
| Outcome: | The proposed model outperforms state-of-the-art summarization models with multi-level memory . the proposed dataset is highly abstractive and outperformed existing models with the proposed model . |
Perspective-taking and Pragmatics for Generating Empathetic Responses Focused on Emotion Causes (2021.emnlp-main)
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| Challenge: | Empathy is a complex cognitive ability based on the reasoning of others’ affective states. |
| Approach: | They propose a method to infer emotion cause words from utterances without a word-level label and a novel method to make dialogue models focus on targeted words in the input during generation. |
| Outcome: | The proposed method improves multiple best-performing dialogue agents on generating more focused empathetic responses in terms of automatic and human evaluation. |
How Robust are Fact Checking Systems on Colloquial Claims? (2021.naacl-main)
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| Challenge: | Existing fact checking systems that perform well on colloquial claims significantly degenerate on collotic claims with the same semantics. |
| Approach: | They propose to transfer the styles of claims from FEVER into colloquialism to investigate fact checking systems on colloqual claims. |
| Outcome: | The proposed system significantly degenerates on colloquial claims with the same semantics. |
AudioCaps: Generating Captions for Audios in The Wild (N19-1)
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| Challenge: | a dataset of 46K audio clips with human-written text pairs is used to generate captions for audio . the task of translating a multimedia input source into natural language has been extensively studied over the past few years . |
| Approach: | They propose a top-down multi-scale encoder and aligned semantic attention for audio captioning. |
| Outcome: | The proposed captions are faithful to audio inputs and better than existing models. |