NeurIPS 2024PastOther
NeurIPS 2024 Workshop on Compositional Learning: Perspectives, Methods, and Paths Forward
Compositional_Learning
- Submission deadline
- Sep 28, 2024, 12:00 UTCimported from OpenReview — check the website for extensions
- Submission portal
- OpenReview
- Notes
- Topics were auto-suggested and may be imprecise — edits welcome.
Accepted papers (41)
Fetched from OpenReview (v2) on 2026-06-10.
A Linear Network Theory of Iterated Learning
A Multimodal Chain of Tools for Described Object Detection
An Integrated Approach to Open-World Compositional Zero-Shot Learning
Can language model plan in extrapolated environments?: Casestudy in textualized Gridworld
Can Models Learn Skill Composition from Examples?
Compositional Communication with LLMs and Reasoning about Chemical Structures
Compositional Few-shot Learning of Motions
Compositional Risk Minimization
Compositional Visual Reasoning with SlotSSMs
ConceptMix: A Compositional Image Generation Benchmark with Controllable Difficulty
CoS: Enhancing Personalization with Context Steering
Crafting Global Optimizers to Reasoning Tasks via Algebraic Objects in Neural Nets
Crosslingual Capabilities and Knowledge Barriers in Multilingual Large Language Models
Diffusion Beats Autoregressive: An Evaluation of Compositional Generation in Text-to-Image Models
Dynamic Symbolic Representation and LLM to Enhance Task Abstraction in Hierarchical Reinforcement Learning
Enhancing Generalization in Sparse Mixture of Experts Models: The Case for Increased Expert Activation in Compositional Tasks
Evaluating Language Models Planning Capabilities on Goal Ordering Challenges
Exploring A Bayesian View On Compositional and Counterfactual Generalization
Faster Slot Decoding using Masked Transformer
From Text to Pose to Image: Improving Diffusion Model Control and Quality
Generating Intermediate Representations for Compositional Text-To-Image Generation
Geometric Signatures of Compositionality in Language Models
GSR-Bench: A Benchmark for Grounded Spatial Reasoning Evaluation via Multimodal LLMs
HAMMR : HierArchical MultiModal React agents for generic VQA
Instruct-SkillMix: A Powerful Pipeline for LLM Instruction Tuning
Latent Concept-based Explanation of NLP Models
Learning Via Imagination: Controlled Diffusion Image Augmentation
Object-Centric Temporal Consistency via Conditional Autoregressive Inductive Biases
OC-CLIP : Object-centric Binding in Contrastive Language-Image Pretraining
Pretraining Frequency Predicts Compositional Generalization of CLIP on Real-World Tasks
Provably Learning Concepts by Comparison
Relational composition during attribute retrieval in GPT is not purely linear
Rule Extrapolation in Language Models: A Study of Compositional Generalization on OOD Prompts
Scalable and interpretable quantum natural language processing: an implementation on trapped ions
Sometimes I am a Tree: Data Drives Fragile Hierarchical Generalization
Successes and Limitations of Object-centric Models at Compositional Generalisation
Towards Object-Centric Learning with General Purpose Architectures
Transformer-based Imagination with Slot Attention
Transformers Can Learn Meta-skills for Task Generalization in In-Context Learning
Understanding Simplicity Bias towards Compositional Mappings via Learning Dynamics
Unraveling the Latent Hierarchical Structure of Language and Images via Diffusion Models