2 citations · 3 across the 8 of their papers we have counts for
8 papers · 1 filter
CompCQR: Compositional Query Generation for Training-Free Conversational Search
Yunah Jang, Kang-il Lee, Joongbo Shin +1
Multi-turn interactions with LLMs are becoming increasingly common in information-seeking scenarios. However, user queries are often ambiguous and context-dependent, making them il…
LLMs can be easily Confused by Instructional Distractions
Yerin Hwang, Yongil Kim, Jahyun Koo +3
Despite the fact that large language models (LLMs) show exceptional skill in instruction following tasks, this strength can turn into a vulnerability when the models are required t…
SWITCH: Studying with Teacher for Knowledge Distillation of Large Language Models
Jahyun Koo, Yerin Hwang, Yongil Kim +3
Despite the success of Large Language Models (LLMs), they still face challenges related to high inference costs and memory requirements. To address these issues, Knowledge Distilla…
AdvisorQA: Towards Helpful and Harmless Advice-seeking Question Answering with Collective Intelligence
Minbeom Kim, Hwanhee Lee, Joonsuk Park +2
As the integration of large language models into daily life is on the rise, there is a clear gap in benchmarks for advising on subjective and personal dilemmas. To address this, we…
MP2D: An Automated Topic Shift Dialogue Generation Framework Leveraging Knowledge Graphs
Yerin Hwang, Yongil Kim, Yunah Jang +3
Despite advancements in on-topic dialogue systems, effectively managing topic shifts within dialogues remains a persistent challenge, largely attributed to the limited availability…
Dialogizer: Context-aware Conversational-QA Dataset Generation from Textual Sources
Yerin Hwang, Yongil Kim, Hyunkyung Bae +3
To address the data scarcity issue in Conversational question answering (ConvQA), a dialog inpainting method, which utilizes documents to generate ConvQA datasets, has been propose…
Weakly Supervised Semantic Parsing with Execution-based Spurious Program Filtering
Kang-il Lee, Segwang Kim, Kyomin Jung
The problem of spurious programs is a longstanding challenge when training a semantic parser from weak supervision. To eliminate such programs that have wrong semantics but correct…
LifeTox: Unveiling Implicit Toxicity in Life Advice
Minbeom Kim, Jahyun Koo, Hwanhee Lee +3
As large language models become increasingly integrated into daily life, detecting implicit toxicity across diverse contexts is crucial. To this end, we introduce LifeTox, a datase…