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AI-Insight

@AI_Insight_Talk

Riding the Wave of the AI Era Together

Katılım Şubat 2024
129 Takip Edilen74 Takipçiler
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AI-Insight
AI-Insight@AI_Insight_Talk·
🚀Top 20 Likes of Hugging Face Daily Paper @_akhaliq @huggingface 🚀Congratulattion huggingface.co/spaces/hysts/d… 1、The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits 2、Qwen2.5 Technical Report 3、MiniMax-01: Scaling Foundation Models with Lightning Attention 4、LLM in a flash: Efficient Large Language Model Inference with Limited Memory 5、Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone 6、Llama 2: Open Foundation and Fine-Tuned Chat Models 7、rStar-Math: Small LLMs Can Master Math Reasoning with Self-Evolved Deep Thinking 8、CLEAR: Character Unlearning in Textual and Visual Modalities 9、EMO: Emote Portrait Alive - Generating Expressive Portrait Videos with Audio2Video Diffusion Model under Weak Conditions 10、GAIA: a benchmark for General AI Assistants 11、GaLore: Memory-Efficient LLM Training by Gradient Low-Rank Projection 12、DocLLM: A layout-aware generative language model for multimodal document understanding 13、3D Gaussian Splatting for Real-Time Radiance Field Rendering 14、Retentive Network: A Successor to Transformer for Large Language Models 15、Differential Transformer 16、Qwen2 Technical Report 17、Mixtral of Experts 18、Transformer Explainer: Interactive Learning of Text-Generative Models 19、Your Transformer is Secretly Linear 20、Self-Rewarding Language Models
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Vincent
Vincent@vansinhu·
Hugging Face Weekly Paper Trends @_akhaliq (Gen by nana-banana-pro)
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AI-Insight
AI-Insight@AI_Insight_Talk·
Found an interesting next model architecture exploration work from Shanghai AI Lab: SDAR, a new paradigm that converts trained AR models into blockwise diffusion models for FAST parallel decoding! ✅ AR's training efficiency ✅ Diffusion's inference speed The 30B MoE model even beats pure AR baselines on GPQA and ChemBench. HF Papers: huggingface.co/papers/2510.06… Model(1.7B/4B/8B/30B-A3B):huggingface.co/collections/Je…
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Qwen
Qwen@Alibaba_Qwen·
🚀 Qwen3-30B-A3B-Thinking-2507, a medium-size model that can think! • Nice performance on reasoning tasks, including math, science, code & beyond • Good at tool use, competitive with larger models • Native support of 256K-token context, extendable to 1M Qwen Chat: Go to  chat.qwen.ai/?model=Qwen3-3…  and click “Thinking”. HF:huggingface.co/Qwen/Qwen3-30B… or huggingface.co/Qwen/Qwen3-30B… ModelScope: modelscope.cn/models/Qwen/Qw… or modelscope.cn/models/Qwen/Qw…
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Vincent
Vincent@vansinhu·
🔥 BREAKTHROUGH ALERT! OpenCompass @OpenCompassX v0.4.1 is now LIVE 🚀 Our latest release brings new Omni-Math support, OlympiadBench evaluation framework, and the challenging HLE dataset! Enhanced math verification, dataset repetition, and G-Pass computation. See how we're pushing the boundaries of AI evaluation! #AIEvaluation #OpenCompass #TechInnovation github.com/open-compass/o…
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Vincent
Vincent@vansinhu·
🚀 Just discovered #WritingBench - a game-changer for evaluating LLMs' writing capabilities! 🔥 Key highlights: • 1,239 queries across 6 domains & 100 subdomains • Dynamic criteria generation with 83% human alignment • Enables 7B models to reach SOTA performance The paper identifies that CoT prompting significantly improves creative writing tasks - something we should all implement! Their domain categorization is incredibly thorough. Check out the repo: github.com/X-PLUG/Writing… #AI #NLP #LLM #Research
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Vincent
Vincent@vansinhu·
🔥MedAgentsBench: Amazing Work🚀 Just explored #MedAgentBench from @Yale researchers and it's mind-blowing! They've created a cutting-edge benchmark that finally exposes the true capabilities of LLMs in complex medical reasoning. ⚡ Key discoveries: DeepSeek R1 & OpenAI O3 dominate clinical reasoning tasks Agent-based frameworks deliver exceptional performance-cost balance Open-source alternatives are closing the gap at fraction of the cost This work shatters previous benchmarks that failed to challenge today's advanced models. The future of medical AI is here: github.com/gersteinlab/me… #MedicalAI #MachineLearning #AIinHealthcare 🔥
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GitHubDaily
GitHubDaily@GitHub_Daily·
一个可视化正则表达式的开源工具:regex-vis。 该工具能够辅助我们学习、编写和验证正则,只需输入一条正则表达式,即可生成可视化图形。 GitHub:github.com/Bowen7/regex-v… 不仅如此,还可以点选或框选图形进行编辑,比如插入节点、进行分组、增加量词等等。
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AI Will
AI Will@FinanceYF5·
微软刚刚发布了OmniParser V2,这改变了一切。 这个AI可以看到你的屏幕,理解它,并采取行动,就像一个人一样。 100%免费且开源!
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AK
AK@_akhaliq·
o3-mini made a working video version prompt: make a app called chatgpt ad maker that takes in a video and does a black and white dotted image effect with sliders to adjust dot size, add a video replay button as well
OpenAI@OpenAI

What do you want to create next?

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Poonam Soni
Poonam Soni@CodeByPoonam·
RIP Sora China just dropped another open-source model: Goku, their Video Generator 13 wild examples so far (Don't miss the 5th one)
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