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Showing papers from KAIST, AITRICS Show all papers

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NeurIPS 2026Korea Advanced Institute of ScieKAISTKAIST, AITRICSMolecules & drug discovery

Synthon Contrastive Learning for Synthesizable 3D Molecule Generation

Nahyun Kim, Seul Lee, Sung Ju Hwang

Atlanta Poster Session 3, Thu, Dec 10, 10:00 AM–1:00 PM, Hall C1 · Published 2026

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2/20 AI panelreviewers recommend it

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AI panel: 2 of 20 reviewers recommend it
lenient 2/5
medium 0/10
strict 0/5
45%Niche pick
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NeurIPS 2026DeepAuto.aiKAISTKAIST, AITRICSTime series forecasting

Visual Anchoring for Scenario-Guided Forecasting

Patara Trirat, Jay Heo, Heejun Lee, Sung Ju Hwang

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

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0/20 AI panelreviewers recommend it

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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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NeurIPS 2026KAIST / MetaNVIDIAKAIST, AITRICSLLM agents & planning

Agent Explorative Policy Optimization for Agentic Multimodal Reasoning

Minki Kang, Shizhe Diao, Ryo Hachiuma, Sung Ju Hwang and 3 more

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

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1/20 AI panelreviewers recommend it

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AI panel: 1 of 20 reviewers recommend it
lenient 1/5
medium 0/10
strict 0/5
72%Highly rated
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NeurIPS 2026Korea Advanced Institute of ScieKAISTKAIST, AITRICSPrivacy

It Takes Two: Complementary Self-Distillation for Contextual Integrity in LLMs

SELFCI uses complementary self-distillation to decouple information suppression from task resolution, improving contextual integrity without degrading utility.

Sangwoo Park, Woongyeong Yeo, Yumin Choi, Hyomin Lee and 5 more

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026 · ▲ 29 on Hugging Face · Code ★ 6

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8/20 AI panelreviewers recommend it

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AI panel: 8 of 20 reviewers recommend it
lenient 5/5
medium 3/10
strict 0/5
78%Highly rated
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NeurIPS 2026Korea Advanced Institute of ScieKAISTKAIST, AITRICSUnified multimodal models

ES-Merging: Biological MLLM Merging via Embedding Space Signals

ES-Merging estimates merging coefficients from embedding space signals to combine biological multimodal models, improving cross-modal reasoning and single-modal knowledge preservation.

Wonbin Lee, Dongki Kim, Sung Ju Hwang

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

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11/20 AI panelreviewers recommend it

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AI panel: 11 of 20 reviewers recommend it
lenient 5/5
medium 6/10
strict 0/5