Every story across every category, newest first. Each card links to the original publisher; daily-brief posts open as editorial pages.
This is very good. I'd say the most impressive attempt at a non-invasive brain recording technology I've seen so far. The end goal is high-resolution ultrasound-based…
Sharing a project I have been working on called Third Eye. It does visual geolocation. Given a video, it figures out where it was filmed using…
Down to $4100 for a new Unitree humanoid modelOne consumer GPU's worthPoe Zhao: Unitree cut its R1 humanoid robot to RMB 29,900 ($4,100). Immediate availability. No…
I want to bring your attention to JetSpec because it looks strictly smarter and stronger than previous speculative decoding and block diffusion approaches (yes, again).Avg 1000…
Curious to hear how long you guys are waiting for a long context session(100k tokens+) to resume in coding agents running locally. submitted by /u/sayamss [link]…
I officially petition my followers and anyone interested who speaks Chinese fluently and might have the chops for this job: Please, try to join DeepSeek. This…
Modern generative world models render increasingly realistic action-controllable futures, yet they frequently hallucinate: rollouts remain visually fluent while drifting from the ground-truth dynamics. We hypothesize that…
A classical intuition holds that verifying a solution is easier than producing one. For today's coding agents, this intuition is being inverted: as foundation models develop…
Vance is just correct. Nixon was a great man of history, a thinker, and his "corruption" was tame and sounds quaint now. Similar power level inflation…
RT vLLMExcited to see @cohere open-source how they use AI coding agents to maintain their vLLM fork. 🙌Keeping a long-lived fork in sync is tricky. Their…
Clueless fools: "AI subscriptions are subsidized! or no, new limits, free lunch is over!"Reality: Arnaud and his likes are *subsidizing Anthropic*I repeat, AI is a very…
> The executives agreed to join on the condition that Sjoerdsma would refrain from raising human rights issues or arms sales to TaiwanMan, the Dutch are…
arXiv:2602.18364v3 Announce Type: replace-cross Abstract: Maximum likelihood prediction (MLP) is a core task at the heart of modern large language models. Here, we study a quantum…
arXiv:2606.26893v1 Announce Type: cross Abstract: We study learning in prophet inequalities with i.i.d. rewards drawn from an exponential-type parametric family with an unknown parameter $theta$, a…
arXiv:2512.19861v2 Announce Type: replace-cross Abstract: Unmeasured confounding can render identification strategies based on adjustment functionals invalid. We study the "Napkin" graph, a causal structure that encapsulates…
arXiv:2606.26815v1 Announce Type: cross Abstract: This paper compares different methods for forecasting the term structure of U.S. and European zero-coupon government bonds using both traditional econometric…
arXiv:2501.07526v2 Announce Type: replace-cross Abstract: Distributed-memory implementations of numerical optimization algorithm, such as stochastic gradient descent (SGD), require interprocessor communication at every iteration of the algorithm.…
arXiv:2606.26772v1 Announce Type: cross Abstract: Differentially private (DP) training of neural networks is often hindered by the large amount of noise required by gradient-based methods such…
arXiv:1906.09235v3 Announce Type: replace-cross Abstract: Along with fruitful applications of Deep Neural Networks (DNNs) to realistic problems, recently, some empirical studies of DNNs reported a universal…
arXiv:2606.26652v1 Announce Type: cross Abstract: In this paper, we study Nystr"om subsampling for vector-valued regression in vector-valued reproducing kernel Hilbert spaces. Standard kernel methods often suffer…
arXiv:2606.27349v1 Announce Type: cross Abstract: Comparing two probability distributions is a basic building block of statistics and machine learning, and the right family is well understood:…
arXiv:2606.26621v1 Announce Type: cross Abstract: Polynomial Stein discrepancies (PSD) provide a scalable alternative to kernel Stein methods for measuring sample quality and goodness-of-fit testing, but their…
arXiv:2606.27298v1 Announce Type: cross Abstract: We study the fundamental problem of learning a high-dimensional Gaussian truncated to an unknown halfspace. Lee, Mehrotra and Zampetakis (FOCS'24) recently…
arXiv:2606.26975v1 Announce Type: new Abstract: Empirical Bayes (EB) estimators can match the first-order asymptotic risk of maximum likelihood (ML) while behaving very differently at second order:…