10 papers
CompLit: Scientific Literature Search Benchmarks Must Cover Implicit, Cumulative, and Unmet Needs
Dayoon Ko, Jihyuk Kim, Soyeong Jeong +6
How much can we trust an agent to find the paper we need? As researchers, we search the literature from what we have read toward what we have not. We thus describe what we want in…
ScholarCatalyst: A Benchmark for Retrieving Papers That Inspire New Research
Sohyeon Kim, Yoonho Lee, Bo Liu +11
What makes great scientists great? Even as AI systems start to make progress on open problems, scientists remain far ahead of them at sensing which prior idea, buried in an ever-gr…
K-BrowseComp: A Web Browsing Agent Benchmark Grounded in Korean Contexts
Nahyun Lee, Dongkeun Yoon, Guijin Son +12
Frontier model evaluations are shifting from foundational capabilities (e.g., instruction following and reasoning) toward compositional, agentic ones, but Korean agentic benchmarks…
When Is Enough Not Enough? Illusory Completion in Search Agents
Dayoon Ko, Jihyuk Kim, Sohyeon Kim +5
In agentic search, an LLM agent searches the web, reads the pages it finds, and decides what to look for next before returning an answer. But can we trust an answer simply because…
Hybrid Deep Searcher: Scalable Parallel and Sequential Search Reasoning
Dayoon Ko, Jihyuk Kim, Haeju Park +6
Large reasoning models (LRMs) combined with retrieval-augmented generation (RAG) have enabled deep research agents capable of multi-step reasoning with external knowledge retrieval…
When Should Dense Retrievers Be Updated in Evolving Corpora? Detecting Out-of-Distribution Corpora Using GradNormIR
Dayoon Ko, Jinyoung Kim, Sohyeon Kim +5
Dense retrievers encode texts into embeddings to efficiently retrieve relevant documents from large databases in response to user queries. However, real-world corpora continually e…
Can LLMs Deceive CLIP? Benchmarking Adversarial Compositionality of Pre-trained Multimodal Representation via Text Updates
Jaewoo Ahn, Heeseung Yun, Dayoon Ko +1
While pre-trained multimodal representations (e.g., CLIP) have shown impressive capabilities, they exhibit significant compositional vulnerabilities leading to counterintuitive jud…
DynamicER: Resolving Emerging Mentions to Dynamic Entities for RAG
Jinyoung Kim, Dayoon Ko, Gunhee Kim
In the rapidly evolving landscape of language, resolving new linguistic expressions in continuously updating knowledge bases remains a formidable challenge. This challenge becomes…
GrowOVER: How Can LLMs Adapt to Growing Real-World Knowledge?
Dayoon Ko, Jinyoung Kim, Hahyeon Choi +1
In the real world, knowledge is constantly evolving, which can render existing knowledge-based datasets outdated. This unreliability highlights the critical need for continuous upd…
Can Language Models Laugh at YouTube Short-form Videos?
Dayoon Ko, Sangho Lee, Gunhee Kim
As short-form funny videos on social networks are gaining popularity, it becomes demanding for AI models to understand them for better communication with humans. Unfortunately, pre…