Unlocking Out-of-Distribution Generalization in Transformers via Recursive Latent Space Reasoning
Fuente:
arXiv
Saved in:
| Main Authors: | Altabaa, Awni, Chen, Siyu, Lafferty, John, Yang, Zhuoran |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
On the Role of Information Structure in Reinforcement Learning for Partially-Observable Sequential Teams and Games
by: Altabaa, Awni, et al.
Published: (2024)
by: Altabaa, Awni, et al.
Published: (2024)
Disentangling and Integrating Relational and Sensory Information in Transformer Architectures
by: Altabaa, Awni, et al.
Published: (2024)
by: Altabaa, Awni, et al.
Published: (2024)
Approximation of relation functions and attention mechanisms
by: Altabaa, Awni, et al.
Published: (2024)
by: Altabaa, Awni, et al.
Published: (2024)
Learning Hierarchical Relational Representations through Relational Convolutions
by: Altabaa, Awni, et al.
Published: (2023)
by: Altabaa, Awni, et al.
Published: (2023)
CoT Information: Improved Sample Complexity under Chain-of-Thought Supervision
by: Altabaa, Awni, et al.
Published: (2025)
by: Altabaa, Awni, et al.
Published: (2025)
Abstractors and relational cross-attention: An inductive bias for explicit relational reasoning in Transformers
by: Altabaa, Awni, et al.
Published: (2023)
by: Altabaa, Awni, et al.
Published: (2023)
PowerFlow: Unlocking the Dual Nature of LLMs via Principled Distribution Matching
by: Chen, Ruishuo, et al.
Published: (2026)
by: Chen, Ruishuo, et al.
Published: (2026)
Decentralized Multi-Agent Reinforcement Learning for Continuous-Space Stochastic Games
by: Altabaa, Awni, et al.
Published: (2023)
by: Altabaa, Awni, et al.
Published: (2023)
On the Design Space Between Transformers and Recursive Neural Nets
by: Chowdhury, Jishnu Ray, et al.
Published: (2024)
by: Chowdhury, Jishnu Ray, et al.
Published: (2024)
Unveiling Induction Heads: Provable Training Dynamics and Feature Learning in Transformers
by: Chen, Siyu, et al.
Published: (2024)
by: Chen, Siyu, et al.
Published: (2024)
NoisyCoconut: Counterfactual Consensus via Latent Space Reasoning
by: Jerge, Michael, et al.
Published: (2026)
by: Jerge, Michael, et al.
Published: (2026)
Enhancing Distribution and Label Consistency for Graph Out-of-Distribution Generalization
by: Wang, Song, et al.
Published: (2025)
by: Wang, Song, et al.
Published: (2025)
ActivationReasoning: Logical Reasoning in Latent Activation Spaces
by: Helff, Lukas, et al.
Published: (2025)
by: Helff, Lukas, et al.
Published: (2025)
LoopQ: Quantization for Recursive Transformers
by: Fang, Rui, et al.
Published: (2026)
by: Fang, Rui, et al.
Published: (2026)
Bridging Reasoning to Learning: Unmasking Illusions using Complexity Out of Distribution Generalization
by: Paqaleh, Mohammad Mahdi Samiei, et al.
Published: (2025)
by: Paqaleh, Mohammad Mahdi Samiei, et al.
Published: (2025)
Recursive Decomposition with Dependencies for Generic Divide-and-Conquer Reasoning
by: Hernández-Gutiérrez, Sergio, et al.
Published: (2025)
by: Hernández-Gutiérrez, Sergio, et al.
Published: (2025)
Identity Bridge: Enabling Implicit Reasoning via Shared Latent Memory
by: Lin, Pengxiao, et al.
Published: (2025)
by: Lin, Pengxiao, et al.
Published: (2025)
Inner Loop Inference for Pretrained Transformers: Unlocking Latent Capabilities Without Training
by: Lys, Jonathan, et al.
Published: (2026)
by: Lys, Jonathan, et al.
Published: (2026)
Sparsity and Out-of-Distribution Generalization
by: Aaronson, Scott, et al.
Published: (2026)
by: Aaronson, Scott, et al.
Published: (2026)
From Words to Actions: Unveiling the Theoretical Underpinnings of LLM-Driven Autonomous Systems
by: He, Jianliang, et al.
Published: (2024)
by: He, Jianliang, et al.
Published: (2024)
Out-of-Distribution Adaptation in Offline RL: Counterfactual Reasoning via Causal Normalizing Flows
by: Cho, Minjae, et al.
Published: (2024)
by: Cho, Minjae, et al.
Published: (2024)
Scalable Power Sampling: Unlocking Efficient, Training-Free Reasoning for LLMs via Distribution Sharpening
by: Ji, Xiaotong, et al.
Published: (2026)
by: Ji, Xiaotong, et al.
Published: (2026)
Latent-Space Contrastive Reinforcement Learning for Stable and Efficient LLM Reasoning
by: Shan, Lianlei, et al.
Published: (2026)
by: Shan, Lianlei, et al.
Published: (2026)
Subgraph Generation for Generalizing on Out-of-Distribution Links
by: Revolinsky, Jay, et al.
Published: (2025)
by: Revolinsky, Jay, et al.
Published: (2025)
Language Models are Hidden Reasoners: Unlocking Latent Reasoning Capabilities via Self-Rewarding
by: Chen, Haolin, et al.
Published: (2024)
by: Chen, Haolin, et al.
Published: (2024)
Embedding Trajectory for Out-of-Distribution Detection in Mathematical Reasoning
by: Wang, Yiming, et al.
Published: (2024)
by: Wang, Yiming, et al.
Published: (2024)
Generative Risk Minimization for Out-of-Distribution Generalization on Graphs
by: Wang, Song, et al.
Published: (2025)
by: Wang, Song, et al.
Published: (2025)
Interaction Locality in Hierarchical Recursive Reasoning
by: Miyanishi, Yosuke, et al.
Published: (2026)
by: Miyanishi, Yosuke, et al.
Published: (2026)
Recursive Inference Machines for Neural Reasoning
by: Komisarczyk, Mieszko, et al.
Published: (2026)
by: Komisarczyk, Mieszko, et al.
Published: (2026)
Out-of-Distribution Generalization for Neural Physics Solvers
by: Wei, Zhao, et al.
Published: (2026)
by: Wei, Zhao, et al.
Published: (2026)
Latent Flow Transformer
by: Wu, Yen-Chen, et al.
Published: (2025)
by: Wu, Yen-Chen, et al.
Published: (2025)
JTreeformer: Graph-Transformer via Latent-Diffusion Model for Molecular Generation
by: Shi, Ji, et al.
Published: (2025)
by: Shi, Ji, et al.
Published: (2025)
Graph VQ-Transformer (GVT): Fast and Accurate Molecular Generation via High-Fidelity Discrete Latents
by: Zheng, Haozhuo, et al.
Published: (2025)
by: Zheng, Haozhuo, et al.
Published: (2025)
Distributionally Robust Graph Out-of-Distribution Recommendation via Diffusion Model
by: Zhao, Chu, et al.
Published: (2025)
by: Zhao, Chu, et al.
Published: (2025)
ThinkRouter: Efficient Reasoning via Routing Thinking between Latent and Discrete Spaces
by: Xu, Xin, et al.
Published: (2026)
by: Xu, Xin, et al.
Published: (2026)
Compute-Optimal Quantization-Aware Training
by: Dremov, Aleksandr, et al.
Published: (2025)
by: Dremov, Aleksandr, et al.
Published: (2025)
Modeling the Data-Generating Process is Necessary for Out-of-Distribution Generalization
by: Kaur, Jivat Neet, et al.
Published: (2022)
by: Kaur, Jivat Neet, et al.
Published: (2022)
Dynamic Large Concept Models: Latent Reasoning in an Adaptive Semantic Space
by: Qu, Xingwei, et al.
Published: (2025)
by: Qu, Xingwei, et al.
Published: (2025)
Causal Negative Sampling via Diffusion Model for Out-of-Distribution Recommendation
by: Zhao, Chu, et al.
Published: (2025)
by: Zhao, Chu, et al.
Published: (2025)
Improving Out-of-Distribution Generalization of Trajectory Prediction for Autonomous Driving via Polynomial Representations
by: Yao, Yue, et al.
Published: (2024)
by: Yao, Yue, et al.
Published: (2024)
Similar Items
-
On the Role of Information Structure in Reinforcement Learning for Partially-Observable Sequential Teams and Games
by: Altabaa, Awni, et al.
Published: (2024) -
Disentangling and Integrating Relational and Sensory Information in Transformer Architectures
by: Altabaa, Awni, et al.
Published: (2024) -
Approximation of relation functions and attention mechanisms
by: Altabaa, Awni, et al.
Published: (2024) -
Learning Hierarchical Relational Representations through Relational Convolutions
by: Altabaa, Awni, et al.
Published: (2023) -
CoT Information: Improved Sample Complexity under Chain-of-Thought Supervision
by: Altabaa, Awni, et al.
Published: (2025)