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Surprisingly Complex Waves Reveal the Brain's Inner Workings
Unexpected patterns traveling across the human brain may be reorganizing its activity in real time.
9 min · 2,113 words
Comparing Muon, NorMuon and AdamW for Fine-tuning a Dense Retriever
Qingcheng Zeng gives Muon and NorMuon the same tuning budget as AdamW when fine-tuning a contrastively pretrained dense retriever: lower training loss, no BEIR win. Learning rate and transfer matter more than the optimizer.
5 min · 1,151 words
Meta FAIR introduces RL-XAR (Reinforcement Learning from eXpert-Aligned Rubrics): learn rubrics from the gap between expert writing and model output, then train models toward expert-level text generation to reduce AI slop.
16 min · 3,572 words
Can a Model Learn New Skills as Add-Ons?
Connito Research trains residual MoE experts with their own routers on a frozen DeepSeek-V2-Lite base, then merges independently trained math, code, medical, law, and finance experts in seconds without retraining—lifting domain benchmarks while leaving the original model untouched.
4 min · 913 words
Throughout the history of AI, open research has played a critical role in driving progress. Today, many key details of frontier large language models (LLMs) remain proprietary, but open-weights model families— such as DeepSeek, Kimi, and MiMo —continue to provide a valuable window into the development process for modern LLMs.
7 min · 1,609 words
“As a Language Model…”: Chat Template Switches LLM Self-Referential Voice
Research showing chat templates act as a switch between disclaimer (“I’m just an AI”) and experiential (“I feel”) self-referential voices across 8 instruct models, with a steerable activation direction that reproduces the template effect.
3 min · 621 words
DeepSeek Elastic Compute (DSec)
# Computer Science > Distributed, Parallel, and Cluster Computing [Submitted on 19 Sep 2026] # Title:DeepSeek Elastic Compute (DSec): A Sandbox Infrastructure for Effective Agentic Training at Scale View PDF HTML (experimental) Abstract:Large-scale agentic training and evaluation with large language models (LLMs) rely on isolated, stateful execution environments in which models inspect repositories, invoke tools, execute commands, and interact with task-specific services. These workloads create sandboxes in large bursts, span heterogeneous functionality and isolation…
16 min · 3,693 words
Exploding variance of means of exponentials: least-squares to the rescue
Francis Bach reframes log-sum-exp / KL estimation as a continuum of least-squares problems with closed-form spectral solutions—cutting exploding exponential variance.
2 min · 464 words
Towards Universal Post-Training for Robotics
Perry Dong and Chelsea Finn on why robotics RL differs from LLM RL, what EXPO-FT gets right and wrong, and what a universal post-training recipe for real-world robots still needs.
15 min · 3,484 words
Mercury 2.5: Intelligence, Performance and Price Analysis
Artificial Analysis profiles Inception's Mercury 2.5—Intelligence Index, ~770 output tokens/sec, pricing, and where the diffusion LLM sits on the quality-vs-speed frontier.
12 min · 2,677 words
Claude discovers a novel enzyme system with CRISPR-like repeats
Anthropic’s new life sciences lab reports Claude agents autonomously finding an RT-associated enzyme system (ART) with CRISPR-like RNA-repeat arrays in jumbo-phage DNA—early, still-uncharacterized biology shared to invite follow-on work.
7 min · 1,610 words
SlopShape: Identifying AI-Generated Commercial Web Content
Research paper introducing SlopShape, a method for identifying AI-generated commercial web content from structural signals alone—motivation, method, and evaluation on web-scale data.
48 min · 11,021 words
What Is RLCD? The Secret Behind Jev
Di Zhang explains RLCD (schema-conditioned Plackett–Luce reward modeling) and how Jev turns calibrated multiway decisions into a product—making the reward model the model rather than hiding it behind a generator.
10 min · 2,324 words
Duality in Optimization: A Visual Tutorial
Mohini Bariya’s arXiv tutorial builds geometric intuition for Lagrangian duality in optimization—bridging solver techniques and solution interpretation with visual explanations of the dual.
1 min · 114 words
The Right Answer Is Not a Proof: Put Verification Inside the Reasoning Loop
Cognaptus explains PRoSFI: a 7B model emits small machine-checkable reasoning steps that Lean/Z3 can verify, raising measured soundness far more than final-answer accuracy alone on ProverQA-Hard.
6 min · 1,480 words
An Empirical Study of Harness Design for Coding Agents
Fan et al. ablate planning, action space, and context management in a fixed coding-agent loop across 176 SWE-Bench/Terminal-Bench settings, finding when context management, planning, and predefined tools help—and when bash-only is enough.
1 min · 291 words
Scaling Discovery through Test-Time Communication
Research paper showing that test-time communication among identical agents sharing discoveries can beat independent parallel search on ARC-AGI-3 and transfer to research tasks like polyomino packing and MNIST compression.
54 min · 12,394 words
Infinite-Parameter LLMs: Generating and Adapting Weights from Live Data
Research proposing infinite-parameter LLMs that generate and adapt weights from live data streams, rather than relying only on a fixed pretrained parameter set.
56 min · 12,974 words
Breaking the 1.58-bit Barrier for Ternary LLMs
Breaking the 1.58-bit Barrier for Ternary LLMs Abstract Ternary Large Language Models (LLM) store every weight as one of three symbols , so the cost of a ternary model is conventionally referenced to the information-theoretic bits per weight. The prevailing deployment format…
34 min · 7,811 words
Asking Authors About Their Own Papers
TMLR Editor-in-Chief Nihar B. Shah interviewed authors of 10 papers slated for desk rejection; many could not answer basic questions about their own submissions as desk-reject rates rose from ~6% to ~53%.
6 min · 1,438 words