:: Library Catalog

Image de couverture de livre

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Park, Simon, Kaur, Simran, Arora, Sanjeev
Format:	Preprint
Publié:	2025
Sujets:	Machine Learning
Accès en ligne:	https://arxiv.org/abs/2512.01775
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Instruct-SkillMix: A Powerful Pipeline for LLM Instruction Tuning
par: Kaur, Simran, et autres
Publié: (2024)

Can Models Learn Skill Composition from Examples?
par: Zhao, Haoyu, et autres
Publié: (2024)

Skill-Targeted Adaptive Training
par: He, Yinghui, et autres
Publié: (2025)

Prioritized Replay for RL Post-training
par: Fatemi, Mehdi
Publié: (2026)

Contextual Drag: How Errors in the Context Affect LLM Reasoning
par: Cheng, Yun, et autres
Publié: (2026)

Optimistic Verifiable Training by Controlling Hardware Nondeterminism
par: Srivastava, Megha, et autres
Publié: (2024)

Countdown-Code: A Testbed for Studying The Emergence and Generalization of Reward Hacking in RLVR
par: Khalifa, Muhammad, et autres
Publié: (2026)

On the Power of Context-Enhanced Learning in LLMs
par: Zhu, Xingyu, et autres
Publié: (2025)

RL Grokking Recipe: How Does RL Unlock and Transfer New Algorithms in LLMs?
par: Sun, Yiyou, et autres
Publié: (2025)

SFT Memorizes, RL Generalizes: A Comparative Study of Foundation Model Post-training
par: Chu, Tianzhe, et autres
Publié: (2025)

The unregulated plant‐based ‘milk’ industry: A threat to nutrition, health and safety?
par: Simran Kaur Arora
Publié: (2024)

Generalizing from SIMPLE to HARD Visual Reasoning: Can We Mitigate Modality Imbalance in VLMs?
par: Park, Simon, et autres
Publié: (2025)

When and How Does CLIP Enable Domain and Compositional Generalization?
par: Kempf, Elias, et autres
Publié: (2025)

Echo Chamber: RL Post-training Amplifies Behaviors Learned in Pretraining
par: Zhao, Rosie, et autres
Publié: (2025)

On the Impossibility of Retrain Equivalence in Machine Unlearning
par: Yu, Jiatong, et autres
Publié: (2025)

On the SDEs and Scaling Rules for Adaptive Gradient Algorithms
par: Malladi, Sadhika, et autres
Publié: (2022)

VAM: Verbalized Action Masking for Controllable Exploration in RL Post-Training -- A Chess Case Study
par: Zhang, Zhicheng, et autres
Publié: (2026)

DUMP: Automated Distribution-Level Curriculum Learning for RL-based LLM Post-training
par: Wang, Zhenting, et autres
Publié: (2025)

CRePE: Convolution-aware Relative Importance in Post-training Pruning with Efficient Search
par: Park, Cheonjun
Publié: (2026)

A Quadratic Synchronization Rule for Distributed Deep Learning
par: Gu, Xinran, et autres
Publié: (2023)

Unrealized Expectations: Comparing AI Methods vs Classical Algorithms for Maximum Independent Set
par: Wu, Yikai, et autres
Publié: (2025)

Metacognitive Reuse: Turning Recurring LLM Reasoning Into Concise Behaviors
par: Didolkar, Aniket, et autres
Publié: (2025)

Trainable Transformer in Transformer
par: Panigrahi, Abhishek, et autres
Publié: (2023)

Provable unlearning in topic modeling and downstream tasks
par: Wei, Stanley, et autres
Publié: (2024)

SkillRL: Evolving Agents via Recursive Skill-Augmented Reinforcement Learning
par: Xia, Peng, et autres
Publié: (2026)

Skill Reuse as Compression in Agentic RL
par: Xu, Zhikun, et autres
Publié: (2026)

JigsawRL: Assembling RL Pipelines for Efficient LLM Post-Training
par: Hu, Zhengding, et autres
Publié: (2026)

LLMStinger: Jailbreaking LLMs using RL fine-tuned LLMs
par: Jha, Piyush, et autres
Publié: (2024)

SCALAR: Learning and Composing Skills through LLM Guided Symbolic Planning and Deep RL Grounding
par: Zabounidis, Renos, et autres
Publié: (2026)

ParallelKittens: Systematic and Practical Simplification of Multi-GPU AI Kernels
par: Sul, Stuart H., et autres
Publié: (2025)

How Does Critical Batch Size Scale in Pre-training?
par: Zhang, Hanlin, et autres
Publié: (2024)

ReSkill: Reconciling Skill Creation with Policy Optimization in Agentic RL
par: He, Zelin, et autres
Publié: (2026)

When Errors Can Be Beneficial: A Categorization of Imperfect Rewards for Policy Gradient
par: Shang, Shuning, et autres
Publié: (2026)

ASAP: Unsupervised Post-training with Label Distribution Shift Adaptive Learning Rate
par: Park, Heewon, et autres
Publié: (2025)

SCOPE-RL: Stable and Quantitative Control of Policy Entropy in RL Post-Training
par: Wang, Chen, et autres
Publié: (2025)

SPEED-RL: Faster Training of Reasoning Models via Online Curriculum Learning
par: Zhang, Ruiqi, et autres
Publié: (2025)

Why is Your Language Model a Poor Implicit Reward Model?
par: Razin, Noam, et autres
Publié: (2025)

Why Does RL Generalize Better Than SFT? A Data-Centric Perspective on VLM Post-Training
par: Lu, Aojun, et autres
Publié: (2026)

ThunderKittens: Simple, Fast, and Adorable AI Kernels
par: Spector, Benjamin F., et autres
Publié: (2024)

Benchmarking and Building Long-Context Retrieval Models with LoCo and M2-BERT
par: Saad-Falcon, Jon, et autres
Publié: (2024)