Copertina

Ranking-aware Reinforcement Learning for Ordinal Ranking

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Hao, Aiming, Zhu, Chen, Zhu, Jiashu, Wu, Jiahong, Chu, Xiangxiang
Natura:	Preprint
Pubblicazione:	2026
Soggetti:	Machine Learning Artificial Intelligence
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Emotions as Ambiguity-aware Ordinal Representations
di: Wu, Jingyao, et al.
Pubblicazione: (2025)

Tree Search for LLM Agent Reinforcement Learning
di: Ji, Yuxiang, et al.
Pubblicazione: (2025)

Decoupling General and Personalized Knowledge in Federated Learning via Additive and Low-Rank Decomposition
di: Wu, Xinghao, et al.
Pubblicazione: (2024)

TROFI: Trajectory-Ranked Offline Inverse Reinforcement Learning
di: Sestini, Alessandro, et al.
Pubblicazione: (2025)

Each Rank Could be an Expert: Single-Ranked Mixture of Experts LoRA for Multi-Task Learning
di: Zhao, Ziyu, et al.
Pubblicazione: (2025)

Omni-Effects: Unified and Spatially-Controllable Visual Effects Generation
di: Mao, Fangyuan, et al.
Pubblicazione: (2025)

Low-Rank Adaptation for Critic Learning in Off-Policy Reinforcement Learning
di: Zhuang, Yuan, et al.
Pubblicazione: (2026)

GPG: A Simple and Strong Reinforcement Learning Baseline for Model Reasoning
di: Chu, Xiangxiang, et al.
Pubblicazione: (2025)

TRAP: Tail-aware Ranking Attack for World-Model Planning
di: Duan, Siyuan, et al.
Pubblicazione: (2026)

R^3: Replay, Reflection, and Ranking Rewards for LLM Reinforcement Learning
di: Jiang, Zhizheng, et al.
Pubblicazione: (2026)

Towards Off-Policy Reinforcement Learning for Ranking Policies with Human Feedback
di: Xiao, Teng, et al.
Pubblicazione: (2024)

Tensor and Matrix Low-Rank Value-Function Approximation in Reinforcement Learning
di: Rozada, Sergio, et al.
Pubblicazione: (2022)

Optimal Policy Sparsification and Low Rank Decomposition for Deep Reinforcement Learning
di: Goddla, Vikram
Pubblicazione: (2024)

Beyond Factor Aggregation: Gauge-Aware Low-Rank Server Representations for Federated LoRA
di: Chen, Jinqian, et al.
Pubblicazione: (2026)

Global Low-Rank, Local Full-Rank: The Holographic Encoding of Learned Algorithms
di: Xu, Yongzhong
Pubblicazione: (2026)

Rank-1 Approximation of Inverse Fisher for Natural Policy Gradients in Deep Reinforcement Learning
di: Huo, Yingxiao, et al.
Pubblicazione: (2026)

Stable-LoRA: Stabilizing Feature Learning of Low-Rank Adaptation
di: Wu, Yize, et al.
Pubblicazione: (2026)

DRSLF: Double Regularized Second-Order Low-Rank Representation for Web Service QoS Prediction
di: Wu, Hao, et al.
Pubblicazione: (2025)

When Is Rank-1 Steering Cheap? Geometry, Granularity, and Budgeted Search
di: Robertson, John T., et al.
Pubblicazione: (2026)

Chiplet Placement Order Exploration Based on Learning to Rank with Graph Representation
di: Deng, Zhihui, et al.
Pubblicazione: (2024)

Riemannian Networks over Full-Rank Correlation Matrices
di: Chen, Ziheng, et al.
Pubblicazione: (2026)

Hybrid-LoRA: Bridging Full Fine-Tuning and Low-Rank Adaptation for Post-Training
di: Zhang, Chengqian, et al.
Pubblicazione: (2026)

Mixture-of-Subspaces in Low-Rank Adaptation
di: Wu, Taiqiang, et al.
Pubblicazione: (2024)

Flora: Low-Rank Adapters Are Secretly Gradient Compressors
di: Hao, Yongchang, et al.
Pubblicazione: (2024)

Calibrated Preference Learning: The Case of Label Ranking
di: Thies, Santo M. A. R., et al.
Pubblicazione: (2026)

Low-Rank Adaptation for Foundation Models: A Comprehensive Review
di: Yang, Menglin, et al.
Pubblicazione: (2024)

Observation-Free Attacks on Online Learning to Rank
di: Chattopadhyay, Sameep, et al.
Pubblicazione: (2025)

Adaptively Learning to Select-Rank in Online Platforms
di: Wang, Jingyuan, et al.
Pubblicazione: (2024)

Embedding-perturbed Exploration Preference Optimization for Flow Models
di: Hu, Sujie, et al.
Pubblicazione: (2026)

AROMA: Autonomous Rank-one Matrix Adaptation
di: Sheng, Hao Nan, et al.
Pubblicazione: (2025)

Low-Rank Compression of Language Models via Differentiable Rank Selection
di: Sundrani, Sidhant, et al.
Pubblicazione: (2025)

ReasonRank: Empowering Passage Ranking with Strong Reasoning Ability
di: Liu, Wenhan, et al.
Pubblicazione: (2025)

A Multi-objective Complex Network Pruning Framework Based on Divide-and-conquer and Global Performance Impairment Ranking
di: Shang, Ronghua, et al.
Pubblicazione: (2023)

Confident Feature Ranking
di: Neuhof, Bitya, et al.
Pubblicazione: (2023)

On the Limitations of Rank-One Model Editing in Answering Multi-hop Questions
di: He, Zhiyuan, et al.
Pubblicazione: (2026)

A Stronger Mixture of Low-Rank Experts for Fine-Tuning Foundation Models
di: Sun, Mengyang, et al.
Pubblicazione: (2025)

AReaL: A Large-Scale Asynchronous Reinforcement Learning System for Language Reasoning
di: Fu, Wei, et al.
Pubblicazione: (2025)

Preference Learning Algorithms Do Not Learn Preference Rankings
di: Chen, Angelica, et al.
Pubblicazione: (2024)

A Survey on E-Commerce Learning to Rank
di: Kabir, Md. Ahsanul, et al.
Pubblicazione: (2024)

QAMRO: Quality-aware Adaptive Margin Ranking Optimization for Human-aligned Assessment of Audio Generation Systems
di: Wang, Chien-Chun, et al.
Pubblicazione: (2025)