Seminar
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The presentation materials for the seminar can be found here.Β
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Debate, Reflect, and Distill: Multi-Agent Feedback with Tree-Structured Preference Optimization for Efficient Language Model EnhancementΒ
λ°νμ: μλ―Όμ£Ό
ποΈ 2025λ 12μ 02μΌ
β° 11:00 ~ 12:30
π FTC 522νΈ
Disentangling and Generating Modalities for Recommendation in Missing Modality ScenariosΒ
λ°νμ: μ νμ
ποΈ 2025λ 12μ 02μΌ
β° 11:00 ~ 12:30
π FTC 522νΈ
Attention Is All You NeedΒ
λ°νμ: κΉμ€μ
ποΈ 2025λ 11μ 25μΌ
β° 11:00 ~ 12:30
π FTC 522νΈ
Agentic Context Engineering: Evolving Contexts for Self-Improving Language Models
λ°νμ: μ΄λν
ποΈ 2025λ 11μ 25μΌ
β° 11:00 ~ 12:30
π FTC 522νΈ
GD-RETRIEVER: CONTROLLABLE GENERATIVE TEXT-MUSIC RETRIEVAL WITH DIFFUSION MODELSΒ
λ°νμ: λ°λμ°
ποΈ 2025λ 11μ 25μΌ
β° 11:00 ~ 12:30
π FTC 522νΈ
Re2LLM: Reflective Reinforcement Large Language Model for Session-based RecommendationΒ
λ°νμ: λ°μ§μΈ
ποΈ 2025λ 11μ 18μΌ
β° 11:00 ~ 12:30
π FTC 522νΈ
Real-Time Detection of Hallucinated Entities in Long-Form GenerationΒ
λ°νμ: μ₯μ’ ν
ποΈ 2025λ 11μ 18μΌ
β° 11:00 ~ 12:30
π FTC 522νΈ
When majority rules, minority loses: bias amplification of gradient descentΒ
λ°νμ: μ΄μ€μ
ποΈ 2025λ 11μ 11μΌ
β° 10:30 ~ 12:00
π FTC 522νΈ
Time-Series Question Answering (TSQA)
λ°νμ: μ΄μ¬μ
ποΈ 2025λ 11μ 11μΌ
β° 10:30 ~ 12:00
π FTC 522νΈ
CLAMP1 & CLAMP2
λ°νμ: κΉμμΈ
ποΈ 2025λ 11μ 04μΌ
β° 10:30 ~ 12:00
π FTC 522νΈ
RL makes MLLMs see better than SFT
λ°νμ: μ μ§μ°
ποΈ 2025λ 11μ 04μΌ
β° 10:30 ~ 12:00
π FTC 522νΈ
Disentangling Biased Knowledge from Reasoning in Large Language Models via Machine UnlearningΒ Β
λ°νμ: μ΄μ€μ
ποΈ 2025λ 10μ 28μΌ
β° 11:00 ~ 12:30
π FTC 522νΈ
Generating with Fairness: A Modality-Diffused Counterfactual Framework for Incomplete Multimodal RecommendationsΒ
λ°νμ: μ νμ
ποΈ 2025λ 10μ 28μΌ
β° 11:00 ~ 12:30
π FTC 522νΈ
Deep Researcher with Test-Time DiffusionΒ
λ°νμ: μ΄λν
ποΈ 2025λ 10μ 14μΌ
β° 10:30 ~ 12:00
π FTC 522νΈ
CrossMuSim: A Cross-Modal Framework for Music Similarity Retrieval with LLM-Powered Text Description Sourcing and MiningΒ Β
λ°νμ: λ°λμ°
ποΈ 2025λ 10μ 14μΌ
β° 10:30 ~ 12:00
π FTC 522νΈ
Harnessing LLMs for Temporal Data - A Study on Explainable Financial Time Series ForecastingΒ
λ°νμ: κΉμ€μ
ποΈ 2025λ 10μ 14μΌ
β° 10:30 ~ 12:00
π FTC 522νΈ
RLPF: Reinforcement Learning from Prediction Feedback for User Summarization with LLMs
λ°νμ: λ°μ§μΈ
ποΈ 2025λ 10μ 02μΌ
β° 14:00 ~ 15:30
π FTC 522νΈ
Why Language Models HallucinateΒ
λ°νμ: μ₯μ’ ν
ποΈ 2025λ 10μ 02μΌ
β° 14:00 ~ 15:30
π FTC 522νΈ
Towards Robust ESG Analysis Against Greenwashing Risks: Aspect-Action Analysis with Cross-Category Generalization
λ°νμ: μ΄μ¬μ
ποΈ 2025λ 09μ 23μΌ
β° 11:00 ~ 12:30
π FTC 522νΈ
Distilling Reasoning Ability From Large Language Models With Adaptive ThinkingΒ
λ°νμ: μλ―Όμ£Ό
ποΈ 2025λ 09μ 23μΌ
β° 11:00 ~ 12:30
π FTC 522νΈ
LLM2CLIP: Powerful Language Model Unlocks Richer Visual Representation Β
λ°νμ: μ μ§μ°
ποΈ 2025λ 09μ 09μΌ
β° 09:30 ~ 11:00
π FTC 522νΈ
Exploring the Feasibility of LLMs for Automated Music Emotion Annotation Β Β
λ°νμ: κΉμμΈ
ποΈ 2025λ 09μ 09μΌ
β° 09:30 ~ 11:00
π FTC 522νΈ
Closed π
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