Workshop
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Relational composition during attribute retrieval in GPT is not purely linear
Michael McCoy · Anna Leshinskaya
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Workshop
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Transformers Can Learn Meta-skills for Task Generalization in In-Context Learning
Ying Fan · Steve Yadlowsky · Dimitris Papailiopoulos · Kangwook Lee
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Workshop
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Geometric Signatures of Compositionality Across a Language Model’s Lifetime
Jin Hwa Lee · Thomas Jiralerspong · Lei Yu · Emily Cheng
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Workshop
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Dynamics of Concept Learning and Compositional Generalization
Yongyi Yang · Core Francisco Park · Ekdeep S Lubana · Maya Okawa · Wei Hu · Hidenori Tanaka
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Workshop
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Sun 8:25
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Compositional Learning: Perspectives, Methods, and Paths Forward
Ying Wei · Jonathan Richard Schwarz · Yilun Du · Laurent Charlin · Mengye Ren · Matthias Bethge
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Workshop
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Can Models Learn Skill Composition from Examples?
Haoyu Zhao · Simran Kaur · Dingli Yu · Anirudh Goyal · Sanjeev Arora
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Workshop
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Sat 12:00
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Cannot or Should Not? Automatic Analysis of Refusal Composition in IFT/RLHF Datasets and Refusal Behavior of Black-Box LLMs
Alexander von Recum · Christoph Schnabl · Gabor Hollbeck · Marvin von Hagen · Silas Alberti · Philip Blinde
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Workshop
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Sun 15:45
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Successes and Limitations of Object-centric Models at Compositional Generalisation
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Workshop
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Sun 9:30
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Lightning Talk: Compositional Generalization Across Distributional Shifts with Sparse Tree Operations
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Workshop
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Dynamic Symbolic Representation and LLM to Enhance Task Abstraction in Hierarchical Reinforcement Learning
Sao Mai Nguyen · Zihe Ji · Mehdi Zadem
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Workshop
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OC-CLIP : Object-centric Binding in Contrastive Language-Image Pretraining
Rim Assouel · Pietro Astolfi · Florian Bordes · Michal Drozdzal · Adriana Romero
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Workshop
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Decompose, Recompose, and Conquer: Multi-modal LLMs are Vulnerable to Compositional Adversarial Attacks in Multi-Image Queries
Julius Broomfield · George Ingebretsen · Reihaneh Iranmanesh · Sara Pieri · Ethan Kosak-Hine · Tom Gibbs · Reihaneh Rabbany · Kellin Pelrine
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