5 papers
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…
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 Is Enough Not Enough? Illusory Completion in Search Agents
Dayoon Ko, Jihyuk Kim, Sohyeon Kim +5
Recent search agents leverage multi-turn reasoning and search tools to achieve strong performance on multi-hop and long-horizon benchmarks. Yet it remains unclear whether they reli…
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…