Amazon

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Verified

https://aws.amazon.com/

AI & ML interests

Scalable Artificial Intelligence

Recent Activity

iknoor26 updated a dataset about 4 hours ago

amazon/InteractivityJudgeBench

iknoor26 published a dataset about 5 hours ago

amazon/InteractivityJudgeBench

s0972456 updated a collection about 21 hours ago

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Papers

Lean4AgenticRL: Advancing Agentic RL with Verifiable Multi-level Process Rewards

ALoDLM: Adaptively Looped Diffusion Language Models

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Articles

Profiling TorchNeuron (Part 1): System-level profiling on AWS Trainium.

Record, train, and deploy from one place with Strands Agents, LeRobot, and Hugging Face Storage Buckets

From Hugging Face to Amazon SageMaker Studio in one click

From the Hugging Face Hub to robot hardware with Strands Agents and LeRobot

Building Blocks for Foundation Model Training and Inference on AWS

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amazon 's papers 44

Submitted by

Ruida WANG

Lean4AgenticRL: Advancing Agentic RL with Verifiable Multi-level Process Rewards

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Submitted by

Liancheng Fang

ALoDLM: Adaptively Looped Diffusion Language Models

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Submitted by

ilgee hong

Training LLM Judges from Language Feedback via Position-Selective Self-Distillation

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Submitted by

Haibo Jin

Breaking Babel: A Self-Evolving Multi-Agent System for Long-Form Subtitle Translation

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2

Hermes: Learning Contextual Reasoning Unlocks Test-Time Scaling

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Submitted by

Nikos Kanakaris

MILO: Automated Harness Discovery via Orchestrated Multi-Agent Evolution

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2

Submitted by

Langlin Huang

On the Off-Policy Teacher in On-Policy Distillation

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Submitted by

Xi Xiao

Rethinking Latent Visual Reasoning: Grounding Latent Reasoning in Visual Evidence

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Submitted by

Sangmin Woo

StructRL: Online Structured Reinforcement Learning for Long-Horizon Vision-Language-Action Tasks

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Submitted by

Aparajith

AutoResearch at Production Scale: Failure Modes and a Multi-Agent Framework

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2

Submitted by

Yuan He

Rufus-Air: An Open LLM Post-Training Recipe

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3

Submitted by

Juzheng Zhang

Don't Mask the Environment: Observation Supervision Changes How Agents Explore Under RL

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