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Showing papers from Hanyang University Show all papers

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EvoDuet: Bilevel Co-Evolution of Web Searching and Task Solving for Scientific Discovery

EvoDuet co-evolves solutions and web queries via a retrieval gate to boost LLM discovery gains up to 82.3% across optimization tasks.

Young-Jun Lee, Jinheon Baek, Soyeong Jeong, Minki Kang and 4 more

Published Sep 30, 2026 · 0 citations · ▲ 109 on Hugging Face · Code ★ 4

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AI panel: 11 of 20 reviewers recommend it
lenient 5/5
medium 5/10
strict 1/5
57%Worth a look
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SDS-LoRA: Overcoming Anisotropic Gradient Scaling in Low-Rank Adaptation

JungHun Oh, Sungyong Baik, Kyoung Mu Lee

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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AI panel: 1 of 20 reviewers recommend it
lenient 1/5
medium 0/10
strict 0/5
67%Highly rated
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Dynamic Context Modeling for Longitudinal Mental Health Monitoring under Distribution Shift

Seungwan Jin, Taehyung Noh, Junghyun Kim, Uichin Lee and 1 more

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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lenient 2/5
medium 0/10
strict 0/5
67%Highly rated
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Right Results, Wrong Reasons: Auditing Behavioral Reliance in Motion Forecasting

Geonyeong Park, Byounghun Park, Nayoung Kim, Kyungmin Kim and 1 more

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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AI panel: 2 of 20 reviewers recommend it
lenient 1/5
medium 0/10
strict 1/5
57%Worth a look
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ReSMap: Recasting Satellite Priors for Robust and Accurate Online HD Map Construction

Kyungmin Kim, Sumin Lee, Sungoh Jeong, DoHyun Lim and 2 more

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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lenient 1/5
medium 0/10
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45%Niche pick
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SPERA: Spherical Prior EEG Foundation Model with Geometry- and Frequency-Aware Latent Prediction

Minsu Kim, Ye-Sung Kim, Hyeseong Jeon, Wooseok Hyung and 2 more

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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How Complete Should a Reference Be? A Benchmark Audit for Fluorescence Spot Detection

Jiyeong Kong, Pan-Gyun Jeong, Kyung-Tae Kang

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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lenient 1/5
medium 0/10
strict 0/5
67%Highly rated
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Task-Aware KV Cache Compression for LLM Agents via Utility-Driven Step Pruning

Yusen Wu, Yefan Wang, Jia Yee Tan, Guangyuan Dong and 5 more

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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AI panel: 2 of 20 reviewers recommend it
lenient 2/5
medium 0/10
strict 0/5
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Beyond FLOPs: Train-Full, Deploy-Partial Multi-Exit Inference via Selective Lightweight IC Ensemble

Bitchan Eom, Eunchan Kim

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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AI panel: 0 of 20 reviewers recommend it
lenient 0/5
medium 0/10
strict 0/5
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Saddle-to-Saddle Dynamics in Self-Supervised Shortcut Learning

Juhwan Kim, yoonsoo nam, Sungyoon Lee

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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ShiftRAG: Bypassing the Textual Bottleneck via Decoupled Learning and Continuous Soft Tokens

Youmin Ko, Jihong Jeong, Hyunjoon Kim

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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AI panel: 0 of 20 reviewers recommend it
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medium 0/10
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57%Worth a look
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Which Tokens to Merge? Diffusion Dynamics for Efficient Image Generation

SeungJu Cha, Ye-Chan Kim, HyunGee Kim, Sungho Koh and 1 more

Atlanta Poster Session 5, Fri, Dec 11, 10:00 AM–1:00 PM, Hall C1 · Published 2026

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AI panel: 1 of 20 reviewers recommend it
lenient 1/5
medium 0/10
strict 0/5
74%Highly rated
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ODDR: One-Step Deshadow Diffusion via Reward Guidance

ODDR achieves efficient, high-fidelity shadow removal without real-world paired supervision via one-step diffusion guided by a synthetic, annotation-free ShadowReward model, approaching fully supervised performance.

Junseong Shin, Kijun Kim, Minseong Kim, Dongjin Kim and 1 more

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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9/20 AI panelreviewers recommend it

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AI panel: 9 of 20 reviewers recommend it
lenient 5/5
medium 4/10
strict 0/5
78%Highly rated
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PickMoment: Continuous-Time Single-Image-to-Video via Learning Deblurring and Blur-to-Video

PickMoment learns continuous-time blur integration via sub-interval mean predictions with additivity and sharp-frame constraints to unify deblurring and video generation in one pass.

Junseong Shin, Hyeonsu Jo, Daehyun Kim, Tae Hyun Kim

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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AI panel: 11 of 20 reviewers recommend it
lenient 4/5
medium 6/10
strict 1/5