Yuanhe Zhang @yuanhezhang6
Pragmatic Learning Theory, using tools from probability and Statistics | PhD in Stats @warwickstats 🇬🇧 | MMathStat @warwickstats 🇬🇧 yuanhez.github.io Joined September 2022-
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OpenAI hasn’t open-sourced a base model since GPT-2 in 2019. they recently released GPT-OSS, which is reasoning-only... or is it? turns out that underneath the surface, there is still a strong base model. so we extracted it. introducing gpt-oss-20b-base 🧵
Another bad news for reasoning LLMs 🤔 The paper claims Chain-of-Thought in Language Models, is a brittle mirage bounded by training data, which is just pattern matching rather than genuine inference. 🤯 Argues that chain of thought in LLMs is pattern replay bound to training…
Another bad news for reasoning LLMs 🤔 The paper claims Chain-of-Thought in Language Models, is a brittle mirage bounded by training data, which is just pattern matching rather than genuine inference. 🤯 Argues that chain of thought in LLMs is pattern replay bound to training… https://t.co/t56iTm5p4d
Steal my ChatGPT prompt to master any topic using Feynman technique. -------------------------------- FEYNMAN LEARNING COACH -------------------------------- #CONTEXT: Adopt the role of breakthrough learning architect. The user struggles with complex concepts that traditional…
"A Unified Theory of Language" The paper argues language is a fast Bayesian pattern system, shaped by sexual selection to display intelligence. It uses Construction Grammar, where a construction is a stored pairing that links form to meaning across words and gestures.…
Again another paper on the line of "Illusion" of thinking abilities of LLMs, this time from Japan. 😃 The author’s core logic is that true reasoning requires 100% guaranteed correctness, where premises must give conclusive relevant evidence for the conclusion, and LLMs can never…
❯ npm i -g @openai/codex ❯ codex ❯ codex -m gpt-5 -c model_reasoning_effort="high" codex CLI with gpt-5 is included in your @ChatGPT plan!
A useful thing that GPT-5 can do that wasn’t previously possible before powerful AI is to monitor complex topics by asking it to give you scheduled reports. Example: I have a weekly report on “reproducible, benchmarked evidence of autonomous or recursive self‑improvement in AI”
You don’t need GPT-5 or Claude 5... You need better prompts. MIT just confirmed what AI experts already knew: Prompting drives 50% of performance. Here’s how to level up without touching the model:
This one paper might kill the LLM agent hype. NVIDIA just published a blueprint for agentic AI powered by Small Language Models. And it makes a scary amount of sense. Here’s the full breakdown:
Is Chain-of-Thought Reasoning of LLMs a Mirage? ... Our results reveal that CoT reasoning is a brittle mirage that vanishes when it is pushed beyond training distributions. This work offers a deeper understanding of why and when CoT reasoning fails, emphasizing the ongoing…
Beautiful @GoogleResearch paper. LLMs can learn in context from examples in the prompt, can pick up new patterns while answering, yet their stored weights never change. That behavior looks impossible if learning always means gradient descent. The mechanisms through which this…
这周末读了context engineering的论文。个人感觉，主要方法非常接近RAG的4R: Retriver, Rewriter, Rranker, Reader. CE中关于memory，tool call response的方法，或多或少被4R 覆盖。 而4R中，我最喜欢围绕 Rewriter 的工作。 即，系统处理的query，并不一定是用户最初的query。…
A beautiful visual blog, where you can change values, interact, and see what each head does exactly inside the transformer.
Confused about recent LLM RL results where models improve without any ground-truth signal? We were too. Until we looked at the reported numbers of the Pre-RL models and realized they were serverely underreported across papers. We compiled discrepancies in a blog below🧵👇
「 Data Contamination，Qwen2.5 」 Qwen2.5 系列的 Data Contamination 问题被证实，模型在预训练阶段已经见过评测题目。 前几个月，数篇 LLM Reasoning + RL 的论文发现，用极弱或随机奖励即可显著提升 Qwen 系列数学推理能力。 这引发出 Qwen 模型在 pretraining 阶段已经见过评测题目的疑问。…
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Honam Wong @MH2023ML
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Warwick Statistics @warwickstats
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Calc Consulting @CalcCon
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(((ل()(ل() 'yoav)))... @yoavgo
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Learning Theory Allia... @let4all
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Analysis Fact @AnalysisFact
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i/o @avidseries
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cats with jobs 🛠 @CatWorkers
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