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20202025
most citedMultimodal Knowledge Alignment with Reinforcement Learning

18 citations · 50 across the 12 of their papers we have counts for

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5 papers · 1 filter

cs.CL202218 cited

Multimodal Knowledge Alignment with Reinforcement Learning

Youngjae Yu, Jiwan Chung, Heeseung Yun +8

Large language models readily adapt to novel settings, even without task-specific training data. Can their zero-shot capacity be extended to multimodal inputs? In this work, we pro…

cs.CL2021

Perspective-taking and Pragmatics for Generating Empathetic Responses Focused on Emotion Causes

Hyunwoo Kim, Byeongchang Kim, Gunhee Kim

Empathy is a complex cognitive ability based on the reasoning of others' affective states. In order to better understand others and express stronger empathy in dialogues, we argue…

cs.CL20203 cited

Augmenting Data for Sarcasm Detection with Unlabeled Conversation Context

Hankyol Lee, Youngjae Yu, Gunhee Kim

We present a novel data augmentation technique, CRA (Contextual Response Augmentation), which utilizes conversational context to generate meaningful samples for training. We also m…

cs.CL2020

Will I Sound Like Me? Improving Persona Consistency in Dialogues through Pragmatic Self-Consciousness

Hyunwoo Kim, Byeongchang Kim, Gunhee Kim

We explore the task of improving persona consistency of dialogue agents. Recent models tackling consistency often train with additional Natural Language Inference (NLI) labels or a…

cs.CL2020

Sequential Latent Knowledge Selection for Knowledge-Grounded Dialogue

Byeongchang Kim, Jaewoo Ahn, Gunhee Kim

Knowledge-grounded dialogue is a task of generating an informative response based on both discourse context and external knowledge. As we focus on better modeling the knowledge sel…