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20212026
most citedMulti-Class Data Description for Out-of-distribution Detection

23 citations · 54 across the 26 of their papers we have counts for

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7 papers · 1 filter

cs.IR2024★ 1 cited

Taxonomy-guided Semantic Indexing for Academic Paper Search

SeongKu Kang, Yunyi Zhang, Pengcheng Jiang +3

Academic paper search is an essential task for efficient literature discovery and scientific advancement. While dense retrieval has advanced various ad-hoc searches, it often strug…

cs.SE2024

Eliciting Instruction-tuned Code Language Models' Capabilities to Utilize Auxiliary Function for Code Generation

Seonghyeon Lee, Suyeon Kim, Joonwon Jang +3

We study the code generation behavior of instruction-tuned models built on top of code pre-trained language models when they could access an auxiliary function to implement a funct…

cs.LG2024

Learning Discriminative Dynamics with Label Corruption for Noisy Label Detection

Suyeon Kim, Dongha Lee, SeongKu Kang +3

Label noise, commonly found in real-world datasets, has a detrimental impact on a model's generalization. To effectively detect incorrectly labeled instances, previous works have m…

cs.IR2024

Multi-Domain Recommendation to Attract Users via Domain Preference Modeling

Hyunjun Ju, SeongKu Kang, Dongha Lee +3

Recently, web platforms have been operating various service domains simultaneously. Targeting a platform that operates multiple service domains, we introduce a new task, Multi-Doma…

cs.SE2024

Exploring Language Model's Code Generation Ability with Auxiliary Functions

Seonghyeon Lee, Sanghwan Jang, Seongbo Jang +2

Auxiliary function is a helpful component to improve language model's code generation ability. However, a systematic exploration of how they affect has yet to be done. In this work…

cs.IR2024

Improving Retrieval in Theme-specific Applications using a Corpus Topical Taxonomy

SeongKu Kang, Shivam Agarwal, Bowen Jin +3

Document retrieval has greatly benefited from the advancements of large-scale pre-trained language models (PLMs). However, their effectiveness is often limited in theme-specific ap…

cs.CL2024★ 1 cited

Pearl: A Review-driven Persona-Knowledge Grounded Conversational Recommendation Dataset

Minjin Kim, Minju Kim, Hana Kim +7

Conversational recommender system is an emerging area that has garnered an increasing interest in the community, especially with the advancements in large language models (LLMs) th…