13 papers
SkillSandbox: Skill Verification via Dynamic Scenario Synthesis
Serin Kim, Kwangwook Seo, Dokyung Song +2
Self-evolving agents distill task-solving experience into skills for future reuse, but these skills can encode incorrect procedures or non-transferable knowledge. It is therefore c…
JudgeCast: Time Series Forecasting with Experience-Informed Covariate Judgements
Donguk Kwon, Wooseok Jeong, Dongha Lee
Covariate effects vary across contexts and shift over time, requiring forecasters to assess how to use them for each forecasting context. As forecasting proceeds, observations for…
Self-Evolving Search Index
Sangam Lee, Wonjae Lee, Sunghwan Kim +5
Information retrieval is increasingly important as LLM agents tackle complex tasks involving diverse information needs. Because retrieval relies on an index that represents each do…
Verified Misguidance: Measuring Structural Citation Failures in Search-Augmented LLMs
Yongsik Seo, Wooseok Jeong, Eunyoung Kim +2
Users of search-augmented LLMs rely on citations as evidence that responses are grounded in real sources, and rarely verify the cited pages themselves. Millions of queries per day…
Persona2Web: Benchmarking Personalized Web Agents for Contextual Reasoning with User History
Serin Kim, Sangam Lee, Dongha Lee
Large language models have advanced web agents, yet current agents lack personalization capabilities. Since users rarely specify every detail of their intent, practical web agents…
SAGEO Arena: A Realistic Environment for Evaluating Search-Augmented Generative Engine Optimization
Sunghwan Kim, Wooseok Jeong, Serin Kim +2
Search-Augmented Generative Engines (SAGE) have emerged as a new paradigm for information access, bridging web-scale retrieval with generative capabilities to deliver synthesized a…
P-Check: Advancing Personalized Reward Model via Learning to Generate Dynamic Checklist
Kwangwook Seo, Dongha Lee
Recent approaches in personalized reward modeling have primarily focused on leveraging user interaction history to align model judgments with individual preferences. However, exist…
Activation Boundary Matching: Task-Informed Initialization for Low-Rank Adaptation
Dongha Lee, Jinhee Park, Minjun Kim +1
Low-Rank Adaptation (LoRA) is highly sensitive to initialization, yet existing schemes construct the initial subspace from statistics at the pretrained point, capturing pre-adaptat…
IPQA: A Benchmark for Core Intent Identification in Personalized Question Answering
Jieyong Kim, Maryam Amirizaniani, Soojin Yoon +1
Intent identification serves as the foundation for generating appropriate responses in personalized question answering (PQA). However, existing benchmarks evaluate only response qu…
Beyond the Final Answer: Evaluating the Reasoning Trajectories of Tool-Augmented Agents
Wonjoong Kim, Sangwu Park, Yeonjun In +3
Although recent tool-augmented benchmarks involve complex requests, evaluation remains limited to answer matching, neglecting critical trajectory aspects like efficiency, hallucina…
Variational Garrote for Statistical Physics-based Sparse and Robust Variable Selection
Hyungjoon Soh, Dongha Lee, Vipul Periwal +1
Selecting key variables from high-dimensional data is increasingly important in the era of big data. Sparse regression serves as a powerful tool for this purpose by promoting model…
BESPOKE: Benchmark for Search-Augmented Large Language Model Personalization via Diagnostic Feedback
Hyunseo Kim, Sangam Lee, Kwangwook Seo +1
Search-augmented large language models (LLMs) have advanced information-seeking tasks by integrating retrieval into generation, reducing users' cognitive burden compared to traditi…
MT-RAIG: Novel Benchmark and Evaluation Framework for Retrieval-Augmented Insight Generation over Multiple Tables
Kwangwook Seo, Donguk Kwon, Dongha Lee
Recent advancements in table-based reasoning have expanded beyond factoid-level QA to address insight-level tasks, where systems should synthesize implicit knowledge in the table t…