Image de couverture de livre

Relational Preference Encoding in Looped Transformer Internal States

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteur principal:	Kirin, Jan
Format:	Preprint
Publié:	2026
Sujets:	Machine Learning Artificial Intelligence
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Vectorized Attention with Learnable Encoding for Quantum Transformer
par: Guo, Ziqing, et autres
Publié: (2025)

Stability and Generalization in Looped Transformers
par: Labovich, Asher
Publié: (2026)

Graph Transformers without Positional Encodings
par: Garg, Ayush
Publié: (2024)

Simple Path Structural Encoding for Graph Transformers
par: Airale, Louis, et autres
Publié: (2025)

Benchmarking Positional Encodings for GNNs and Graph Transformers
par: Grötschla, Florian, et autres
Publié: (2024)

LoopQ: Quantization for Recursive Transformers
par: Fang, Rui, et autres
Publié: (2026)

To CoT or To Loop? A Formal Comparison Between Chain-of-Thought and Looped Transformers
par: Xu, Kevin, et autres
Publié: (2025)

Comparative Explanations: Explanation Guided Decision Making for Human-in-the-Loop Preference Selection
par: Chakraborty, Tanmay, et autres
Publié: (2025)

Rethinking Time Encoding via Learnable Transformation Functions
par: Chen, Xi, et autres
Publié: (2025)

When and How Human Curation Backfires: Preference Alignment under Multi-Model Self-Consuming Loop
par: Zhang, Yang, et autres
Publié: (2026)

Neural ODE Transformers: Analyzing Internal Dynamics and Adaptive Fine-tuning
par: Tong, Anh, et autres
Publié: (2025)

MEP: Multiple Kernel Learning Enhancing Relative Positional Encoding Length Extrapolation
par: Gao, Weiguo
Publié: (2024)

Towards Empirical Interpretation of Internal Circuits and Properties in Grokked Transformers on Modular Polynomials
par: Furuta, Hiroki, et autres
Publié: (2024)

IRPM: Intergroup Relative Preference Modeling for Pointwise Generative Reward Models
par: Song, Haonan, et autres
Publié: (2026)

Encoding Agent Trajectories as Representations with Sequence Transformers
par: Tsiligkaridis, Athanasios, et autres
Publié: (2024)

Inner Loop Inference for Pretrained Transformers: Unlocking Latent Capabilities Without Training
par: Lys, Jonathan, et autres
Publié: (2026)

What Makes Looped Transformers Perform Better Than Non-Recursive Ones
par: Gong, Zixuan, et autres
Publié: (2025)

Should We Ever Prefer Decision Transformer for Offline Reinforcement Learning?
par: Omori, Yumi, et autres
Publié: (2025)

FlowerFormer: Empowering Neural Architecture Encoding using a Flow-aware Graph Transformer
par: Hwang, Dongyeong, et autres
Publié: (2024)

Looping Back to Move Forward: Recursive Transformers for Efficient and Flexible Large Multimodal Models
par: Xu, Ruihan, et autres
Publié: (2026)

Can Looped Transformers Learn to Implement Multi-step Gradient Descent for In-context Learning?
par: Gatmiry, Khashayar, et autres
Publié: (2024)

Memory-Efficient Looped Transformer: Decoupling Compute from Memory in Looped Language Models
par: Vendrell, Victor Conchello, et autres
Publié: (2026)

Reasoning with Latent Thoughts: On the Power of Looped Transformers
par: Saunshi, Nikunj, et autres
Publié: (2025)

Alignment Revisited: Are Large Language Models Consistent in Stated and Revealed Preferences?
par: Gu, Zhuojun, et autres
Publié: (2025)

Relational Graph Transformer
par: Dwivedi, Vijay Prakash, et autres
Publié: (2025)

Imagine Beyond! Distributionally Robust Auto-Encoding for State Space Coverage in Online Reinforcement Learning
par: Castanet, Nicolas, et autres
Publié: (2025)

Bypassing the Exponential Dependency: Looped Transformers Efficiently Learn In-context by Multi-step Gradient Descent
par: Chen, Bo, et autres
Publié: (2024)

Algebraic Positional Encodings
par: Kogkalidis, Konstantinos, et autres
Publié: (2023)

Subjective Logic Encodings
par: Vasilakes, Jake, et autres
Publié: (2025)

SEE: Sememe Entanglement Encoding for Transformer-bases Models Compression
par: Zhang, Jing, et autres
Publié: (2024)

Naga: Vedic Encoding for Deep State Space Models
par: Schaller, Melanie, et autres
Publié: (2025)

Simulation of Graph Algorithms with Looped Transformers
par: de Luca, Artur Back, et autres
Publié: (2024)

RT-Transformer: The Transformer Block as a Spherical State Estimator
par: Racioppo, Peter
Publié: (2026)

Fairness Begins with State: Purifying Latent Preferences for Hierarchical Reinforcement Learning in Interactive Recommendation
par: Lu, Yun, et autres
Publié: (2026)

Confidence Optimization for Probabilistic Encoding
par: Xia, Pengjiu, et autres
Publié: (2025)

Rotary Position Encodings for Graphs
par: Reid, Isaac, et autres
Publié: (2025)

LoopUS: Recasting Pretrained LLMs into Looped Latent Refinement Models
par: Park, Taekhyun, et autres
Publié: (2026)

On the Internal Representations of Graph Metanetworks
par: Yeom, Taesun, et autres
Publié: (2025)

Loop, Think, & Generalize: Implicit Reasoning in Recurrent-Depth Transformers
par: Kohli, Harsh, et autres
Publié: (2026)

Enhancing Graph Transformers with Hierarchical Distance Structural Encoding
par: Luo, Yuankai, et autres
Publié: (2023)