What the smart people are recommending. 7861 books, tools, and products endorsed by the thinkers absorb.md tracks. Ranked by how many times each has been recommended across compiled podcasts, papers, posts, and tweets.
βthis work introduces A-THENA, a lightweight early intrusion detection system (EIDS) that significantly extends preliminary findings on time-aware encodings.β
βyosha bju had a very interesting paper on this in the 2000s using neural Nets to do this actually it was probably one of the first anywayβ
βTo support reproducibility and further research, we will publicly release our evaluation benchmark, preference training dataset, and code at https://pegah-kh.github.io/projects/prompts-override-visionβ¦β
βTo support reproducibility and further research, we will publicly release our evaluation benchmark, preference training dataset, and code at https://pegah-kh.github.io/projects/prompts-override-visionβ¦β
βIt has become clear that Hartigan's algorithm (1975) gives better results in almost all casesβ
βTelgarsky-Vattani note a typical improvement of 5% -- 10%.β
βIn this paper, we present a transferable learning approach for PINNs premised on a fast Pseudoinverse PINN framework (Pi-PINN).β
βunless you are not paying attention to anything in Quantum there was a huge research paper that IBM came out with it was published in nature can you talk a little bit about the significance when I reaβ¦β
βIn this work, we introduce CSA-Graphs, a privacy-preserving structural dataset.β
βIt is called Smartphones, Online Music Streaming, and Traffic Fatalities.β
βOur experiments demonstrate that SAE-SPLADE achieves retrieval performance comparable to SPLADE on both in-domain and out-of-domain tasks while offering improved efficiency.β
βTo address this, we introduce OptiVerse, a comprehensive benchmark... OptiVerse will serve as a foundational platform for advancing LLMs in solving complex optimization challenges.β
βAmanda mole wrote this great piece and Bloomberg highly recommend checking that out.β
βThe code and models will be made publicly available.β
βProject website, videos and code: https://scout-comm.github.io/β
β# Self-Supervised Learning of Split Invariant Equivariant Representationsβ
βThis repository contains the environments in our paper: > [SECANT: Self-Expert Cloning for Zero-Shot Generalization of Visual Policies](https://linxifan.github.io/secant-site/)β
βI do think it's it's potentially The Next Step there's uh there's this idea that'll give you a link to learn more about that yeah yeah I think read the S4 the S4 paperβ
βI really enjoyed the New Yorker profile by Josh Rothman who I've worked with in the pastβ
βthe density matrix prescription by Brody and Graefe [Phys. Rev. Lett. 109, 230405 (2012)]β
βIn this paper, we present Cornetto, the first benchmark to evaluate LLM-driven network configuration repair functionally and at scale.β
βTo read our write-up in full, see here: https://www.anthropic.com/features/project-dealβ
βMore on CursorBench: https://cursor.com/blog/cursorbenchβ
βIn a recent work [Phys. Rev. B 111, 214503 (2025)] we derived the quantum phase dynamics from a many-body treatment which leads to an effective gate voltage-dependent Hamiltonianβ
βabsolutely! here's how we do it: https://openai.com/index/unlocking-the-codex-harness/β
βAcademic papers ARE recommendations if someone is telling the reader to read them (type=paper).β
β# Need is All You Need: Homeostatic Neural Networks Adapt to Concept Shiftβ
βWe expand existing LM-based exploration (El-Naggar et al., 2025a,b) with a simple CL variant and find that CL substantially impacts the apparent inductive bias of LMs.β
βLast year, she co-wrote a report titled Building a More Effective, Responsive Government, Lessons Learned from the Biden-Harris Administration.β
βEverybody loves entropy, yet somehow we are always working hard to reduce it. http://quantumfrontiers.com/2026/04/12/how-i-learned-to-stop-worrying-andno-ive-always-adored-entropy/β
βFind out more β https://deepmind.google/blog/ai-co-clinician/β
βTo address these limitations, we propose COMLLM, a generative framework that enables foresighted decision-making in MEC systems.β
βWe demonstrate this by integrating GIST with two substantially different existing methods, LaDeCo and Design-o-meter.β
βWe demonstrate this by integrating GIST with two substantially different existing methods, LaDeCo and Design-o-meter.β
βWe introduce TensorFlow Quantum (TFQ), an open source library for the rapid prototyping of hybrid quantum-classical models for classical or quantum data.β
βWe present a quantum kernel method for high-dimensional data analysis using Google's universal quantum processor, Sycamore.β
βA combination of self-aggrandizement and elitism has convinced American universities that our services are worth indebting generations of young people, and now risking becoming agents of spread. #nomeβ¦β
βAs the search continues for useful applications of noisy intermediate scale quantum devices, variational simulations of fermionic systems remain one of the most promising directions. Here, we perform β¦β
βI was quoted a couple times in this Atlantic article, but that isnβt (the only) reason I think it is good. It lays out the reasons why we whipsawed from βAI is a bubbleβ to βthere are not enough data β¦β
βHere we explore which heuristic quantum algorithms for combinatorial optimization might be most practical to try out on a small fault-tolerant quantum computer.β
β# Resolving catastrophic error bursts from cosmic rays in large arrays of superconducting qubitsβ
βfuller writeup: https://www.latent.space/p/ainews-agents-for-everything-elseβ
βNew blog post on coordination, collusion, decentralization and forking: https://t.co/8aB7T9NsjTβ
βIn this work, we develop intuitive constructions for a large class of these algorithms based on connections to simple dynamics of quantum systems, quantum walks, and classical continuous relaxations.β
βGiven a quantum circuit, a quantum computer can sample the output distribution exponentially faster in the number of bits than classical computers. A similar exponential separation has yet to be estabβ¦β
βSo you recently posted a paper, "STaR: Bootstrapping Reasoning With Reasoning."β
βThe use of quantum computing for machine learning is among the most exciting prospective applications of quantum technologies.β
βand i'd recommend you go to uh on vitalik.ca i have this article called a quadratic payments a primer and highly recommended it's kind of at least my attempt so far and explaining the intuition behindβ¦β
βi'd recommend the casper ffg paperβ
βCompanion paper arXiv:2603.20997 (Basu, 2026) defines the routing diagnostic task.β
βVery Deep Convolutional Networks for Large-Scale Image Recognition - please cite this paper if you use the VGG models in your work.β
βDeep Residual Learning for Image Recognition - please cite this paper if you use the ResNet model in your work.β
βRethinking the Inception Architecture for Computer Vision - please cite this paper if you use the Inception v3 model in your work.β
β# A hierarchical loss and its problems when classifying non-hierarchicallyβ
βWe propose CRAFT (Clustered Regression for Adaptive Filtering of Training data), a vectorization-agnostic selection method for training sequence-to-sequence models.β
βNew monster post: my own current perspective on the recent debates around techno-optimism, AI risks, and ways to avoid extreme centralization in the 21st century. https://vitalik.eth.limo/general/202β¦β
βBlog post by Yann LeCunβ
βTo resolve these challenges, we propose MADE-IT (Manifold-Aware Dynamic Expert Evolution and Implicit rouTing), an adaptive CMM method...β
βIn this paper, we present pliable rejection sampling (PRS), a new approach to rejection sampling, where we learn the sampling proposal using a kernel estimator.β
β(Calandriello et al. 2016) propose INK-Estimate, an algorithm that processes the dataset incrementally and updates RLS, effective dimension, and Nystrom approximations on-the-fly.β
βIn this paper we introduce SQUEAK, a new algorithm that builds on INK-Estimate but uses unnormalized RLS.β
βA comprehensive simulation study shows that the conformalized SL achieves valid finite-sample coverage with competitive performance relative to the true data-generating mechanism. A central contributiβ¦β
βWe introduce HiLight, an Evidence Emphasis framework that decouples evidence selection from reasoning for frozen LLM solvers. HiLight avoids compressing or rewriting the input, which can discard or diβ¦β
βThe increasing adoption of AI systems in hiring has raised concerns about algorithmic bias and accountability, prompting regulatory responses including the EU AI Act, NYC Local Law 144, and Colorado'sβ¦β
βThe increasing adoption of AI systems in hiring has raised concerns about algorithmic bias and accountability, prompting regulatory responses including the EU AI Act, NYC Local Law 144, and Colorado'sβ¦β
βThe increasing adoption of AI systems in hiring has raised concerns about algorithmic bias and accountability, prompting regulatory responses including the EU AI Act, NYC Local Law 144, and Colorado'sβ¦β
βAudio samples are available at https://qiangchunyu.github.io/UniSonate/.β
βIn this paper, we formulate routing as a budget allocation problem and identify marginal gain... we propose RouteLMT (routing for LLM-based MT), an efficient in-model router... Extensive experiments dβ¦β
βIn this whitepaper, we introduce the Snake Optimizer for efficiently and quickly solving such optimization problems by leveraging concepts in artificial intelligence, dynamic programming, and graph opβ¦β
β# Focus beyond quadratic speedups for error-corrected quantum advantageβ
βProject page: https://muzhancun.github.io/preprints/DROL.β
βyou had a really good post on your blog saying endnotes on 2020 and it was about a lot more than just cryptoβ
βHere, by measuring the time-dependent evolution and fluctuation of out-of-time-order correlators, we experimentally investigate the dynamics of quantum scrambling on a 53-qubit quantum processor. We eβ¦β
β# Implicit Rank-Minimizing Autoencoderβ
β_ArXiv paper co-authored by Hartmut Neven_β
βWe propose Hyperparameter-Divergent Ensemble Training (HDET), a method that repurposes these replicas for simultaneous learning rate exploration at negligible communication overhead.β
βWe demonstrate the application of the Google Sycamore superconducting qubit quantum processor to combinatorial optimization problems with the quantum approximate optimization algorithm (QAOA).β
βWe propose a quantum algorithm for inferring the molecular nuclear spin Hamiltonian from time-resolved measurements of spin-spin correlators, which can be obtained via nuclear magnetic resonance (NMR)β¦β
βyou know for me i've read the alan turing 1950 paper computing machinery and intelligence paper back before i knew how to code and i remember reading it you know it lays out the turing test but then iβ¦β
βBig techβs impending march into higher ed will bring more learning to more humans, and erode our humanity. #nomercynomalice https://www.profgalloway.com/post-corona-higher-ed/β
βWe introduce SOB (The Structured Output Benchmark), a multi-source benchmark spanning three source modalities: native text, images, and audio conversations.β
βI've long objected to the 'surveillance advertising' trope, for it trivializes actual surveillance under force of government, such as this, brought to us by the folks at Palantir. Gift link.β
βWe test whether the causal inner product of \citet{park2024linear} -- defined by the unembedding covariance $Ξ£$ -- enables cross-lingual concept transport.β
βHere, we simulate the dynamics of the one-dimensional Fermi-Hubbard model using 16 qubits on a digital superconducting quantum processor. We observe separations in the spreading velocities of charge aβ¦β
βwell I read papers that's what people should be writing uh generally science papers uh that's where the knowledge is and I will that's where the knowledge will likely remainβ
β# Do Robots powered by a Quantum Processor have the Freedom to swerve? _ArXiv paper co-authored by Hartmut Neven_β
β# A quantum algorithm for training wide and deep classical neural networks _ArXiv paper co-authored by Hartmut Neven_β
βQuantum many-body systems display rich phase structure in their low-temperature equilibrium states. However, much of nature is not in thermal equilibrium.β
βDaario from Anthropic put out this blog post on his website called the adolescence of technology in January of 2026...The loop has already started and we will accelerate rapidly in the coming months aβ¦β
βRemarkable @DIEZEIT story: a researcher brings a last letter from a communist executed by the Nazis to the daughter he never knew.β
βresolve the open question of Gaillard, Gerchinovitz, Huard, and Stoltz, \emph{``Uniform regret bounds over $\mathbb{R}^d$ for the sequential linear regression problem with the square loss''} (ALT 2019β¦β
βHere, we describe a protocol for using a fault-tolerant quantum computer to calculate stopping power from a first-quantized representation of the electrons and projectile. Our approach builds upon theβ¦β
βThese posts from 2016-17 basically advocating for someone to build Uniswap.β
β# Optimizing quantum gates towards the scale of logical qubitsβ
βIf you find the work useful in your research, please cite the DeepTraffic paperβ
βWe introduce Perturb-and-Correct (P&C), a post-hoc method for constructing epistemically diverse predictors from a single pretrained network.β
βWe introduce Personalized RewardBench, a novel benchmark designed to rigorously assess reward models' capacity to model personalized preferences.β
βWe present Basis Selection with Importance (BSI), a principled low-rank compression framework that ranks and prunes bases by directly estimating the expected loss increase incurred when each basis is β¦β
β_Blog post by Yann LeCun_β
β# Sampling diverse near-optimal solutions via algorithmic quantum annealingβ