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Welcome! :tada: on Shital Shah's Chain of Thought

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Articole: 200

  1. Hyperparams for 23 Architectures

    (Welcome! :tada: on Shital Shah's Chain of Thought)

  2. Large Activation Outliers

    (Welcome! :tada: on Shital Shah's Chain of Thought)

  3. One Percent, One Week

    (Welcome! :tada: on Shital Shah's Chain of Thought)

  4. Phi-2: Smol Is More Powerful

    (Welcome! :tada: on Shital Shah's Chain of Thought)

  5. Looped Transformers

    (Welcome! :tada: on Shital Shah's Chain of Thought)

  6. Mamba Paper

    (Welcome! :tada: on Shital Shah's Chain of Thought)

  7. Thermodynamics of Prediction

    (Welcome! :tada: on Shital Shah's Chain of Thought)

  8. Scaling MLPs Paper

    (Welcome! :tada: on Shital Shah's Chain of Thought)

  9. Matmul and Strassen's Algo

    (Welcome! :tada: on Shital Shah's Chain of Thought)

  10. LLMs and Planning

    (Welcome! :tada: on Shital Shah's Chain of Thought)

  11. Announcement: PhD Internship for LLM Evaluation

    (Welcome! :tada: on Shital Shah's Chain of Thought)

  12. Phi-2: Smol but Mighty

    (Welcome! :tada: on Shital Shah's Chain of Thought)

  13. Thankuritto

    (Welcome! :tada: on Shital Shah's Chain of Thought)

  14. MathVista Benchmark

    (Welcome! :tada: on Shital Shah's Chain of Thought)

  15. Loss Scaling in FP16 Training

    (Welcome! :tada: on Shital Shah's Chain of Thought)

  16. Stability's 3B Model Training Report

    (Welcome! :tada: on Shital Shah's Chain of Thought)

  17. Architecture vs Auto-regressive Objective

    (Welcome! :tada: on Shital Shah's Chain of Thought)

  18. Phi-1: The Tiny Model Outsmarting Giants

    (Welcome! :tada: on Shital Shah's Chain of Thought)

  19. Reasoning AWOL? Paper Claims Only ICL Emerged

    (Welcome! :tada: on Shital Shah's Chain of Thought)

  20. Weight Averaging: Have Your Cake and Save Your Model

    (Welcome! :tada: on Shital Shah's Chain of Thought)

  21. Phi-nomenal Code Gen: Phi-1-Base Beats August Models

    (Welcome! :tada: on Shital Shah's Chain of Thought)

  22. Weaving Longer Contexts: Yarn Scaling for LLMs

    (Welcome! :tada: on Shital Shah's Chain of Thought)

  23. Tensor Shape-Shifting: See Shapes Before Values

    (Welcome! :tada: on Shital Shah's Chain of Thought)

  24. Tiny Weights, Mighty Models: The Mystery of Weight Decay

    (Welcome! :tada: on Shital Shah's Chain of Thought)

  25. Conquering FP16 Frustrations: One-Liner to FP8 Gold on H100s

    (Welcome! :tada: on Shital Shah's Chain of Thought)

  26. Creativity on Sale, Reasoning Still Full Price

    (Welcome! :tada: on Shital Shah's Chain of Thought)

  27. Out-Knuthing Knuth: The AGI Test

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  28. The Great 5G Disguise

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  29. Learning Rates Without Fortune Telling

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  30. LLAMA's Math Leap: From 11% to 49% with Scaling

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  31. Descartes in Motion: God, Matter, and Not a Moment's Rest

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  32. UnIVAL: Beyond Words and Pictures

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  33. ChatGPT Rates Your Data: 4.5 Stars or You're Out

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  34. Full Theater, Empty Story: Disappointed by Oppenheimer

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  35. LLM Jailbreaks: Scrambled Words, Still Served Hot

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  36. When Math Gets Abstract: The 6th Grade Shift

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  37. GPT-4's Code Regression: From Prodigy to Buggy

    (Welcome! :tada: on Shital Shah's Chain of Thought)

  38. Blurring Modalities: AI Models Merge Inputs and Outputs

    (Welcome! :tada: on Shital Shah's Chain of Thought)

  39. Claude-2 Fails Hinton's Pop Quiz; GPT-4 Aces It

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  40. When Hackers Crashed the Mainframe Party

    (Welcome! :tada: on Shital Shah's Chain of Thought)

  41. Mosaic's Magic: MI250 Now 'Just Works' at 80% of A100

    (Welcome! :tada: on Shital Shah's Chain of Thought)

  42. From Command Lines to Commanding Visuals: AI's Multimodal Jump

    (Welcome! :tada: on Shital Shah's Chain of Thought)

  43. AI Goes Multimodal: From Textual DOS to Visual Windows

    (Welcome! :tada: on Shital Shah's Chain of Thought)

  44. Understanding "Understanding": Quantifying AI Comprehension

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  45. Tiny but Mighty: MSR's Small Models Crush HumanEval

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  46. When Turing Split the Atom (and the Bit)

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  47. No Free Lunch: The Out-of-Distribution Dilemma

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  48. Machine Learning's Algorithmic Groundhog Day

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  49. Web Giants: Users Do the Heavy Lifting

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  50. Little LSTM Outsmarts Big Transformer in Flip-Flop Task

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