All entries

1/ Excited to report we have a new paper out @Nature today! The bottom line: training data for LLMs does not just fall from the sky - it is created in the context of existing social political institut

AI21 Labs discusses four common agent optimization methods used to balance accuracy against cost and latency constraints. The post indicates the team evaluated all four approaches, likely covering tec

arXiv:2605.11405v1 Announce Type: new Abstract: Data curation has shifted the quality-compute frontier for language-model and contrastive image-text pretraining, but its role for vision-language model

$20/month. Builder: Pinecone's new plan for teams that have outgrown the free tier but aren't running production workloads at scale yet. The prototype-to-production gap has always been an awkward plac

arXiv:2605.11367v1 Announce Type: new Abstract: Recent advances in visual generative models have highlighted the promise of learning generative world models. However, most existing approaches frame wo

arXiv:2605.12437v1 Announce Type: new Abstract: Retrospective novel view synthesis (NVS) of dynamic scenes is fundamental to applications such as sports. Recent dynamic 3D Gaussian Splatting (3DGS) ap

arXiv:2605.11489v1 Announce Type: cross Abstract: 3D Gaussian Splatting (3DGS) enables high-quality real-time 3D rendering but faces challenges in efficiently scaling to ultra-dense scenes and high-re

4/5 Best-of-N: Run one agent config N times in parallel → select the best trajectory. Leverages LLMs’ non-determinism - but hinges on a good eval mechanism (we use an LLM-as-a-Judge). Can increase acc

arXiv:2605.12027v1 Announce Type: new Abstract: Reconstructing dynamic 4D scenes from monocular videos is a fundamental yet challenging task. While recent 3D foundation models provide strong geometric

5/5 Ensemble: Run multiple distinct agent configs in parallel → select the best trajectory. Leverages success of the portfolio vs single variants (see also: @/karpathy’s LLM Council). Can outperform b

7,000 false positives per square millimeter. The culprit was the lab gloves. University of Michigan researchers just upended a core assumption in microplastics science. Latex and nitrile gloves, worn

A belated Mother's Day spotlight on a builder worth celebrating. Sarra is a technical writer and mom in Montréal who came to Replit with one goal: turn screen time into something her kids could create

arXiv:2605.11406v1 Announce Type: new Abstract: Existing granular-ball classification methods are often driven by handcrafted quality measures, neighborhood rules, or heuristic splitting and stopping

arXiv:2605.12328v1 Announce Type: new Abstract: Data entry systems remain structurally vulnerable to categorical misclassifications, particularly in small and medium sized enterprises (SMEs). When nom

arXiv:2605.12438v1 Announce Type: new Abstract: When adapting an encoder to a new domain, the standard approach is to continue training with Masked Language Modeling (MLM). We show that temporarily sw

arXiv:2605.12395v1 Announce Type: new Abstract: Background: Many different approaches to controlled text generation (CTG) have been proposed over recent years, but it is difficult to get a clear pictu

arXiv:2605.11010v1 Announce Type: new Abstract: Federated Learning has emerged as a transformative paradigm for collaborative machine learning across distributed environments. However, its performance

arXiv:2605.11233v1 Announce Type: new Abstract: Effective model selection is critical in symbolic regression (SR) to identify mathematical expressions that balance accuracy and complexity, and have lo

LTX-2.3 is an open-source video generation model released in January 2026 that supports LoRA fine-tuning for customizing styles, characters, and use cases. The Reddit post compiles available LTX-2.3 m

arXiv:2605.11558v1 Announce Type: new Abstract: Activation functions play a central role in neural networks by shaping internal representations. Recently, learning binary activation representations ha

arXiv:2506.23723v2 Announce Type: replace Abstract: The adoption of mobile robotic platforms in complex environments, such as agricultural settings, requires these systems to exhibit a flexible yet ef

arXiv:2605.11554v1 Announce Type: new Abstract: Task-agnostic structure proxies are often used to interpret why one pretraining corpus transfers better than another, but such explanations require the

a dude who plays fast and loose with a nonprofit’s money like this is going to play fast and loose with you future. it’s time to boycott OpenAI. 🚨 OpenAI's original board REJECTED Altman's Helion deal

arXiv:2605.11847v1 Announce Type: cross Abstract: Analog content-addressable memories (aCAMs) based on memristors provide a promising pathway toward energy-efficient large-scale associative computing

arXiv:2509.25239v3 Announce Type: replace-cross Abstract: Chain of thought (CoT) elicits reasoning in large language models by explicitly generating intermediate tokens. In contrast, latent thought re

A little talk on what we can learn from implementing LLM architectures from scratch in Python and PyTorch. And how I approach new open-weight models, compare them against reference implementations etc

A lot of people have been wondering about Mythos, Glasswing, and the vulns we / our partners are fixing. Today, I’m excited for us to start sharing more. (For context, I lead Glasswing @AnthropicAI.)

arXiv:2605.11492v1 Announce Type: new Abstract: Adversarial attacks fool deep image classifiers by adding tiny, almost invisible noise patterns to a clean image. The standard ell^infty-bounded attacks

arXiv:2605.11585v1 Announce Type: new Abstract: This paper addresses the problem of image denoising for grayscale images. We propose a probabilistic image generative model that combines a quadtree reg

A new Database product based on @ApacheDataFusio was announced today from @LangChain -- focused on agent observability. It is really neat to see how people are building (very) customized data + query

arXiv:2605.12350v1 Announce Type: new Abstract: Lack of transparency in AI systems poses challenges in critical real-life applications. It is important to be able to explain the decisions of an AI sys

U.S. Space Command concluded its 'Apollo Insight' wargame in March 2026, with Russia's alleged nuclear anti-satellite capability as the focus scenario. Over 60 defense contractors, government agencies

arXiv:2605.11759v1 Announce Type: cross Abstract: Dimensionality reduction is essential in simulation-based shape design, where high-dimensional parameterizations hinder optimization, surrogate modeli

Varda Space Industries, a startup that’s been pitching its ability to perform drug experiments in space, says it has signed up the pharmaceutical company United Therapeutics in what may be remembered

Bloomberg: A profile of California Rep. Ro Khanna, who spent years cheering on the tech industry and now supports a 5% billionaire wealth tax and stricter AI regulations — Ro Khanna spent years cheeri

arXiv:2605.11247v1 Announce Type: new Abstract: This paper presents a proof-of-concept digital twin framework for simulation-driven diabetes modeling using benchmark clinical data, synthetic temporal

arXiv:2605.11674v1 Announce Type: new Abstract: We compare three state-of-the-art proprioceptive state estimators for quadruped robots: MUSE [1], the Invariant Extended Kalman Filter (IEKF) [2], and t

arXiv:2605.12461v1 Announce Type: cross Abstract: We propose an algorithm to sample from composite log-concave distributions over R^d, i.e., densities of the form pipropto e^{-f-g}, assuming access to

arXiv:2605.12387v1 Announce Type: cross Abstract: Automatic detection of speaker confidence is critical for adaptive computing but remains constrained by limited labelled data and the subjectivity of

arXiv:2605.11513v1 Announce Type: new Abstract: Knowledge Distillation (KD) is a critical tool for training Large Language Models (LLMs), yet the majority of research focuses on approaches that rely s

arXiv:2604.00626v2 Announce Type: replace-cross Abstract: As Large Language Models (LLMs) continue to grow in both capability and cost, transferring frontier capabilities into smaller, deployable stud

A survey predicted that 43% of companies would be deploying AI at scale by the current date, but actual adoption has reached only 19%, indicating a significant gap between forecasted and realized AI i

arXiv:2605.11021v1 Announce Type: new Abstract: This paper develops a switching-system interpretation of Q-learning with linear function approximation (LFA) based on the joint spectral radius (JSR). W

arXiv:2602.02133v2 Announce Type: replace-cross Abstract: Autoregressive language models (ARMs) suffer from the reversal curse: after learning ''A is B,'' they often fail on the reverse query ''B is A

arXiv:2605.11302v1 Announce Type: cross Abstract: We study language generation in the limit under a global preference ordering on strings, as introduced by Kleinberg and Wei. As in [arXiv:2504.14370,

arXiv:2605.11989v1 Announce Type: new Abstract: Transfer learning is a machine learning technique that uses previously acquired knowledge from a source domain to enhance learning in a target domain by