NeurIPS 2024 Past Other

NeurIPS 2024 Workshop on Compositional Learning: Perspectives, Methods, and Paths Forward

Compositional_Learning

Submission deadline
Sep 28, 2024, 12:00 UTC
imported from OpenReview — check the website for extensions
Submission portal
OpenReview
Notes
Auto-imported from the OpenReview venue record on 2026-06-10 — please verify and enrich (topics are keyword-guessed).

Accepted papers (41)

Fetched from OpenReview (v2) on 2026-06-10.

  1. A Linear Network Theory of Iterated Learning

    Devon Jarvis, Richard Klein, Benjamin Rosman, Andrew M Saxe · PDF
  2. A Multimodal Chain of Tools for Described Object Detection

    Kwanyong Park, Youngwan Lee, Yong-Ju Lee · PDF
  3. An Integrated Approach to Open-World Compositional Zero-Shot Learning

    Hirunima Jayasekara, Khoi Pham, Nirat Saini, Abhinav Shrivastava · PDF
  4. Can language model plan in extrapolated environments?: Casestudy in textualized Gridworld

    Doyoung Kim, Jongwon Lee, Jinho Park, Minjoon Seo · PDF
  5. Can Models Learn Skill Composition from Examples?

    Haoyu Zhao, Simran Kaur, Dingli Yu, Anirudh Goyal, Sanjeev Arora · PDF
  6. Compositional Communication with LLMs and Reasoning about Chemical Structures

    Sarathkrishna Swaminathan, Dmitry Zubarev · PDF
  7. Compositional Few-shot Learning of Motions

    Omkar Patil, Anant Sah, Nakul Gopalan · PDF
  8. Compositional Risk Minimization

    Divyat Mahajan, Mohammad Pezeshki, Ioannis Mitliagkas, Kartik Ahuja, Pascal Vincent · PDF
  9. Compositional Visual Reasoning with SlotSSMs

    Jindong Jiang, Fei Deng, Gautam Singh, Minseung Lee, Sungjin Ahn · PDF
  10. ConceptMix: A Compositional Image Generation Benchmark with Controllable Difficulty

    Xindi Wu, Dingli Yu, Yangsibo Huang, Olga Russakovsky, Sanjeev Arora · PDF
  11. CoS: Enhancing Personalization with Context Steering

    Sashrika Pandey, Jerry Zhi-Yang He, Mariah L Schrum, Anca Dragan · PDF
  12. Crafting Global Optimizers to Reasoning Tasks via Algebraic Objects in Neural Nets

    Yuandong Tian · PDF
  13. Crosslingual Capabilities and Knowledge Barriers in Multilingual Large Language Models

    Lynn Chua, Badih Ghazi, Yangsibo Huang, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Amer Sinha, Chulin Xie, Chiyuan Zhang · PDF
  14. Diffusion Beats Autoregressive: An Evaluation of Compositional Generation in Text-to-Image Models

    Arash Mari Oriyad, Parham Rezaei, Mahdieh Soleymani Baghshah, Mohammad Hossein Rohban · PDF
  15. Dynamic Symbolic Representation and LLM to Enhance Task Abstraction in Hierarchical Reinforcement Learning

    Sao Mai Nguyen, Zihe Ji, Mehdi Zadem · PDF
  16. Enhancing Generalization in Sparse Mixture of Experts Models: The Case for Increased Expert Activation in Compositional Tasks

    Jinze Zhao, Junjie Yang, Peihao Wang, Yingbin Liang, Zhangyang Wang · PDF
  17. Evaluating Language Models Planning Capabilities on Goal Ordering Challenges

    Eran Hirsch, Guy Uziel, Ateret Anaby Tavor · PDF
  18. Exploring A Bayesian View On Compositional and Counterfactual Generalization

    Patrik Reizinger, Rahul Krishnan · PDF
  19. Faster Slot Decoding using Masked Transformer

    Akihiro Nakano, Masahiro Suzuki, Yutaka Matsuo · PDF
  20. From Text to Pose to Image: Improving Diffusion Model Control and Quality

    Clément Bonnet, Ariel N. Lee, Franck Wertel, Antoine Tamano, Tanguy Cizain, Pablo Ducru · PDF
  21. Generating Intermediate Representations for Compositional Text-To-Image Generation

    Ran Galun, Sagie Benaim · PDF
  22. Geometric Signatures of Compositionality in Language Models

    Thomas Jiralerspong, Jin Hwa Lee, Lei Yu, Emily Cheng · PDF
  23. GSR-Bench: A Benchmark for Grounded Spatial Reasoning Evaluation via Multimodal LLMs

    Navid Rajabi, Jana Kosecka · PDF
  24. HAMMR : HierArchical MultiModal React agents for generic VQA

    Lluis Castrejon, Thomas Mensink, Howard Zhou, Vittorio Ferrari, Andre Araujo, Jasper Uijlings · PDF
  25. Instruct-SkillMix: A Powerful Pipeline for LLM Instruction Tuning

    Simran Kaur, Simon Park, Anirudh Goyal, Sanjeev Arora · PDF
  26. Latent Concept-based Explanation of NLP Models

    Xuemin Yu, Fahim Dalvi, Nadir Durrani, Marzia Nouri, Hassan Sajjad · PDF
  27. Learning Via Imagination: Controlled Diffusion Image Augmentation

    Judah A Goldfeder, Patrick Minwan Puma, Gabriel Guo, Gabriel Guerra Trigo, Hod Lipson · PDF
  28. Object-Centric Temporal Consistency via Conditional Autoregressive Inductive Biases

    Cristian Meo, Akihiro Nakano, Mircea Tudor Lică, Aniket Rajiv Didolkar, Masahiro Suzuki, Anirudh Goyal, Mengmi Zhang, Justin Dauwels, Yutaka Matsuo, Yoshua Bengio · PDF
  29. OC-CLIP : Object-centric Binding in Contrastive Language-Image Pretraining

    Rim Assouel, Pietro Astolfi, Florian Bordes, Michal Drozdzal, Adriana Romero-Soriano · PDF
  30. Pretraining Frequency Predicts Compositional Generalization of CLIP on Real-World Tasks

    Thaddäus Wiedemer, Yash Sharma, Ameya Prabhu, Matthias Bethge, Wieland Brendel · PDF
  31. Provably Learning Concepts by Comparison

    Yujia Zheng, Shaoan Xie, Kun Zhang · PDF
  32. Relational composition during attribute retrieval in GPT is not purely linear

    Michael B. McCoy, Anna Leshinskaya · PDF
  33. Rule Extrapolation in Language Models: A Study of Compositional Generalization on OOD Prompts

    Anna Mészáros, Szilvia Ujváry, Wieland Brendel, Patrik Reizinger, Ferenc Huszár · PDF
  34. Scalable and interpretable quantum natural language processing: an implementation on trapped ions

    Tiffany Duneau, Saskia Bruhn, Gabriel Matos, Tuomas Laakkonen, Katerina Saiti, Anna Pearson, Konstantinos Meichanetzidis, Bob Coecke · PDF
  35. Sometimes I am a Tree: Data Drives Fragile Hierarchical Generalization

    Tian Qin, Naomi Saphra, David Alvarez-Melis · PDF
  36. Successes and Limitations of Object-centric Models at Compositional Generalisation

    Milton L. Montero, Jeffrey Bowers, Gaurav Malhotra · PDF
  37. Towards Object-Centric Learning with General Purpose Architectures

    Jack Brady, Julius von Kügelgen, Sebastien Lachapelle, Simon Buchholz, Thomas Kipf, Wieland Brendel · PDF
  38. Transformer-based Imagination with Slot Attention

    Yosuke Nishimoto, Takashi Matsubara · PDF
  39. Transformers Can Learn Meta-skills for Task Generalization in In-Context Learning

    Ying Fan, Steve Yadlowsky, Dimitris Papailiopoulos, Kangwook Lee · PDF
  40. Understanding Simplicity Bias towards Compositional Mappings via Learning Dynamics

    Yi Ren, Danica J. Sutherland · PDF
  41. Unraveling the Latent Hierarchical Structure of Language and Images via Diffusion Models

    Antonio Sclocchi, Noam Itzhak Levi, Alessandro Favero, Matthieu Wyart · PDF