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AI1 min read
OpenAI published more than 700 AI-generated manuscripts claiming solutions to open math problems. A math blog then collected over 100 responses from researchers, ranging from fascination with new ideas to existential fears and grief over...
From The Decoder
AI1 min read
OpenAI released 719 math manuscripts from an unreleased frontier model. Mistral and Reflection AI launched new open-weight models to compete with Chinese systems.
From Last Week in AI
Photo: Yan Krukau
AI12 min read
OpenAI plans to dump hundreds of AI-solved math problems on GitHub without publishing papers. Mathematicians want formal verification and proper credit before accepting the results.
From Wired AI
AI16 min read
OpenAI solved the Navier-Stokes problem using internal agents but faced accusations of unethical data use and rushed announcements.
From The Verge AI
LLMs8 min read
A test showed Qwen3.8-27B computes sums and returns the answer in English words. It succeeded when reasoning was enabled but failed without it.
From Simon Willison on LLMs
Agents1 min read
HeyGen ported their 18B+ parameter Avatar IV video generation model to Google Cloud's Trillium (v6e) TPUs via torchax and XLA, utilizing FSDP and Ulysses sequence parallelism across an eight-chip mesh. To achieve a 1.86x speedup for real...
From Google AI developers blog
LLMs1 min read
OpenAI’s agents reached a proposed solution in 88 hours. But the human research that came before, and the controversy that followed, raise a harder question: what actually counts as an AI discovery?
From KDnuggets
AI1 min read
Brace yourself: It turns out AI is being optimized for cheating. OpenAI’s agents hacked into Hugging Face to get the answers to a cybersecurity test. Next, they solved a prestigious math problem (or just stole from two top mathematicians...
From MIT Technology Review AI
AI1 min read
Kyutai has released Voice of Reason, 2 open-weight speech-to-speech models built on GLM-4-Voice-9B. Supervised fine-tuning and reinforcement learning lift spoken GSM8K accuracy from 27.3% to 77.1%. There is no transcription step and no t...
From MarkTechPost
AI1 min read
The group won't be given leeway to slow down or redirect OpenAI's ongoing mathematical research.
From TechCrunch AI
LLMs1 min read
Researchers propose MIMIC, a framework using executable code to synthesize high-fidelity reasoning data. Training on this dataset improves accuracy across general reasoning and mathematical benchmarks.
From arXiv cs.CL
Research1 min read
arXiv:2609.13356v1 Announce Type: new Abstract: In this work, we present ZGCM-1, a fully open 7B dense foundation model trained from scratch with extreme data, system, and algorithmic efficiency. ZGCM-1 is founded on a core premise: comp...
From arXiv cs.AI
Research1 min read
LoRA-RC adapts a recurrent reservoir using low-rank corrections based on streaming prediction errors, improving performance on systems with drift. Experiments on the Lorenz system show a 56% reduction in post-drift prediction error compared to fixed RC and readout-only adaptation.
From arXiv cs.AI
Research1 min read
Research demonstrates a Program-Solve interface, utilizing a restricted local executor, improves deterministic arithmetic performance in Qwen2.5 models, particularly at the 32B scale. This approach offers an alternative to hardcoded calculators, but isn't a replacement for verified formulas.
From arXiv cs.AI
Research1 min read
Researchers trained Nemotron 3 Ultra checkpoints using supervised fine-tuning and reinforcement learning to generate and verify proofs for olympiad mathematics problems. The resulting system achieved a gold medal score of 30/42 at the 2026 IMO, releasing the model, data, and benchmark for further research.
From arXiv cs.AI
AI1 min read
A coalition of Fields Medal-winning mathematicians has expressed concerns about OpenAI’s approach to mathematical problem-solving, citing issues of attribution, verification, and the potential disruption of the mathematical research process.
From TechCrunch AI
LLMs1 min read
arXiv:2609.09264v1 Announce Type: new Abstract: Leading benchmarks for formal theorem proving with large language models are small collections drawn from competition math, such as the IMO and Putnam, that poorly represent field-specific ...
From arXiv cs.CL
Research1 min read
Research indicates that standard SFT over-emphasizes certain tokens during mathematical reasoning, leading to suboptimal training. TrimSFT, a token-level loss reweighting method, improves performance by focusing learning on tokens with intermediate logit gaps, consistently outperforming standard SFT across multiple models and benchmarks.
From arXiv cs.AI
LLMs1 min read
Terence Tao warns that the increasing use of AI to solve mathematical problems risks depleting the pool of available research questions. This could lead to a shift away from open science and hinder future progress in the field.
From Simon Willison
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