Hugging Face has acquired the robotics startup Pollen Robotics, according to Fortune. https://
fortune.com/2025/04/14/ai-
company-hugging-face-buys-humanoid-robot-company-pollen-robotics-reachy-2/
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@jiqizhixin
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Hugging Face acquires robotics startup Pollen Robotics
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DeepSeek Open-Sources AI Inference Engine for Multi-Platform Deployment
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"Our ultimate aim is to foster a synchronized ecosystem where cutting-edge AI capabilities can be seamlessly implemented across diverse hardware platforms upon official model releases."
Link: https://
github.com/deepseek-ai/op
en-infra-index/tree/main/OpenSourcing_DeepSeek_Inference_Engine
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DeepSeek Open-Sources Inference Engine, Announces Ecosystem Collaborations
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DeepSeek has published "The Path to Open-Sourcing the DeepSeek Inference Engine".
In this release, the team outlines their roadmap for open-sourcing and announces upcoming collaborations with existing open-source projects to advance the broader AI infrastructure ecosystem. -
Large Language Models May Be Rote Learners, Not Understanding
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It challenges the assumption that memorization implies understanding.
Large Language Models Could Be Rote Learners
Link：
https://
arxiv.org/pdf/2504.08300 -
LLMs Show Lower Performance on Memorized Multiple-Choice Questions
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Large language models exhibit lower performance on memorized multiple-choice questions compared to non-memorized ones.
This counterintuitive finding suggests the coexistence of two distinct learning mechanisms: rote memorization and genuine capability acquisition. -
Concise Reasoning via Reinforcement Learning
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Concise Reasoning via Reinforcement Learning Paper: https://
arxiv.org/abs/2504.05185 -
Scaling Reasoning in Diffusion Large Language Models via RL
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d1: Scaling Reasoning in Diffusion Large Language Models via Reinforcement Learning
Paper: https://
dllm-reasoning.github.io/media/preprint
.pdf
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Project Page: https://
dllm-reasoning.github.io
Code: https://
github.com/dllm-reasoning
/d1
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GRPO Adapted for Diffusion LLMs: UCLA and Meta’s diffu-GRPO
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Can GRPO work for diffusion LLMs (dLLMs)?
A team from UCLA and Meta says yes—and they’ve got the receipts.
They introduce d1, a framework that adapts pre-trained masked dLLMs into reasoning models via SFT + RL.
The twist? Their RL method is a fresh one: diffu-GRPO. -
Seed-Thinking-v1.5: Advanced AI Model Capabilities Showcase
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Now, can you imagine how strong Seed-Thinking-v1.5 will be?
Seed-Thinking-v1.5: https://
github.com/ByteDance-Seed
/Seed-Thinking-v1.5/blob/main/seed-thinking-v1.5.pdf
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DAPO: https://
arxiv.org/abs/2503.14476
VAPO: -
ByteDance DAPO VAPO Reasoning Models SOTA Algorithms
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Recently, ByteDance created 2 RL algorithms for buliding reasoning models: DAPO and VAPO. According to the tech report of Seed-Thinking-v1.5, VAPO now stands as the SOTA solution in value-based methods, while DAPO establishes a new SOTA result for value-free approaches.