Author

Hwanjo Yu

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Preprint Aug 2026

From Overlooked to Explored: Recovering Item Relations via Mixture of Perspectives for Sequential Recommendation

Capturing user preference from a user's interaction sequence is the central challenge of Sequential Recommendation (SR). This preference intuitively emerges from inter-item relations: each item transition reflects a preference embedded in the relations between items, making the faithful capture of these relations essen...

Junyoung Kim, Wonbin Kweon, Woojoo Kim et al. · 2 citations

#artificial intelligence Preprint Oct 2026

Why, Where, How: Taxonomy-guided Error Grounding for Code Repair in NL2SQL

SQL queries that large language models write from natural language questions can execute successfully yet produce incorrect results, so execution alone does not reveal what to fix. An error taxonomy says why the query is wrong, but not where to look or how to change it. Existing methods can guide SQL correction through...

Su-Chan Lee, Woo-Min Song, Hwanjo Yu et al. · 0 citations

#artificial intelligence Preprint Sep 2026

Difficulty-Adaptive Tree-Structured Policy Optimization for Expanding Reasoning Coverage in RLVR

DATPO (Difficulty-Adaptive Sentence-entropy-guided Tree-structured Policy Optimization) integrates difficulty-adaptive tree search with a sibling-diversity advantage term, explicitly promoting semantic diversity to expand reasoning coverage during training.

Young Kyu Yu, Sanghwan Jang, Hwanjo Yu · 2 citations

Open access Aug 2026

Personalized federated recommendation via long-horizon local optimization and regularized knowledge guidance

A model-agnostic framework that forms personalized item embeddings through Long-Horizon Local Optimization and injects common global knowledge through intermittent Regularized Knowledge Guidance is proposed and Adaptive Guidance is introduced to control the influence of global knowledge at the user–item interaction lev...

Jaehyung Lim, Wonbin Kweon, Woojoo Kim et al. · Journal of Intelligence and... · 0 citations

Preprint Aug 2026

RA-VLA: Retrieval-Augmented VLA for Test-Time Adaptation

RA-VLA is presented, a retrieval-augmented VLA framework that integrates behavior-aligned context retrieval with a grounded execution pipeline that facilitates seamless task adaptation while preserving inference efficiency.

Sanghwan Jang, Minjin Jeon, Minsoo Kim et al. · 1 citation

Preprint Aug 2026

GOD: Enhancing Generalization via Deep Grafting for Sequential Recommendation

Graft-Oriented Distillation (GOD) is proposed, a component-level distillation framework for improved generalization through grafting, which uses selected frozen-teacher components with trainable student counterparts to build hybrid source models.

Woojoo Kim, Junyoung Kim, Jaehyung Lim et al. · 1 citation

#machine learning Preprint Aug 2026

Personalized and Multi-View Representation for Federated Cold-Start Recommendation

PMFRec learns a personalized representation generator to produce user-specific item representations from attribute features, and introduces a global multi-view encoder with item-adaptive gating and an orthogonality objective to capture complementary semantic views while reducing cross-view redundancy.

Jaehyung Lim, Wonbin Kweon, Woojoo Kim et al. · 0 citations

#artificial intelligence Preprint Aug 2026

ReWEIGH the Evidence: Calibrating Token-Level Ordinal Visual Evidence to Mitigate Hallucinations in Large Vision-Language Models

ReWEIGH is a training-free decoding intervention that aggregates vocabulary ranks across visual positions and compares each candidate with a token-specific reference estimated from unlabeled images and applies a bounded penalty only to candidates that fall below their reference.

Jihae Jeong, Jun-Ha Choi, Hwanjo Yu · 0 citations