Knowledge catalogue
You can't solve real-world physical tasks through autoregressive sampling alone. The physical world is entirely unforgiving to hallucination or approximate pattern matching. If we want actual autonomo
A worthwhile (and unnerving) reminder from Anthropic that we should be paying attention to AI ability thresholds, not just steady climbs In this case, the threshold is the capability needed for a self
I'm a first year ML PhD at a T5 ML program in the US. I managed to get a first author paper accepted to NeurIPS Main Track last month and thought I'd start applying for PhD research internships since
The reality for most organizations is that data lives everywhere. As engineering teams expand and adopt specialized platforms for their workloads, enterprise data naturally disperses across multiple c
Sovereign AI control is becoming a business continuity issue as autonomous agents take on essential enterprise workflows. Keeping data within national boundaries addresses part of the challenge, but o
Exa just passed $100m in annualized revenue. We've grown almost exactly 10x per year for 3 years. We now handle 2 billion requests a month from 200k+ teams. And it’s still so early: We predict agents
France's AI ecosystem has moved from ambition to application, from the factory floor to orbit. Ahead of #NVIDIAGTC Berlin, France-based companies are showing what agentic AI on NVIDIA infrastructure a
Many months in the making, MNX is finally live! Whether the AI bubble bursts or not, AI is changing our lives forever. I'm in awe of how this technology has reached something close to escape velocity.
I'm sure some here read this at the time and remember, but I recently found this hilarious Guardian article from 2019 through Wikipedia: https://www.theguardian.com/technology/2019/feb/14/elon-musk-ba
Americans have big concerns about artificial intelligence, but that hasn’t stopped OpenAI Inc., Nvidia Corp., IBM Corp. and others from charging ahead. Last week saw shares of Nvidia, CoreWeave Inc.,
Suggestion for you: Pick an agent for work, and pick an agent for personal. You could explore to do this all with Grok Bot (with many different types of bots) Personally, I like @bot for work, and @Mu
This is my new favorite way to keep up with AI papers. I turn my curated papers into a 2-minute spoken technical briefing with @FishAudio Drama 3, straight from Codex. In the demo, I took one of my fa
(1/7) I'd like to provide some additional context for the remarks that can be found in this interview. (2/7) My discomfort with the attention being paid to existential risk---and with the ongoing domi
arXiv:2610.13479v1 Announce Type: new Abstract: Generating edge case scenarios is crucial for training, testing and safety assuring autonomous systems. This identifies hazardous failures to increase s
Aaron Holmes / The Information: A profile of Microsoft EVP of Copilot Charles Lamanna, a potential Satya Nadella successor; a source says Microsoft is on track to pay Anthropic $2B+ per year — In the
arXiv:2610.13669v1 Announce Type: new Abstract: Curriculum learning typically organizes training samples from easy to hard. In GRPO, medium-difficulty samples are attractive for online selection becau
arXiv:2610.12500v1 Announce Type: cross Abstract: Alzheimer's disease (AD) remains a major public health challenge, and early identification is crucial for timely intervention and care planning. Recen
arXiv:2610.13303v1 Announce Type: cross Abstract: LLM judges are increasingly deployed as panels, and disagreement among panel members is often read as a symptom of an unclear rubric. We test a label-
arXiv:2610.12843v1 Announce Type: cross Abstract: Fewer latent tokens promise cheaper diffusion. Yet aggressive latent compression creates a reconstruction-generation dilemma: adding channels improves
arXiv:2610.12919v1 Announce Type: cross Abstract: We consider online binary prediction with paid stochastic features, where the learner can spend resources to obtain better observations of the underly
arXiv:2610.12520v1 Announce Type: cross Abstract: The goal of circuit discovery is to decompose a monolithic neural network into tiny modular subnetworks which are interpretable in the sense that each
arXiv:2610.13439v1 Announce Type: cross Abstract: Collective Autonomous Vehicle (AV) route choices in real-world traffic networks can create externalities for Human-Driven Vehicles (HDVs), as routes t
arXiv:2610.13144v1 Announce Type: new Abstract: LLM-based multi-agent systems (MAS) have emerged as a promising paradigm for enhancing complex reasoning through role specialization and collaboration,
arXiv:2610.13606v1 Announce Type: cross Abstract: Correlation matrices combine nonlinear positive-definiteness constraints with a simultaneous row-column permutation symmetry. Their generation therefo
arXiv:2610.12775v1 Announce Type: cross Abstract: The two main traditional player statistics used in soccer are goals scored and assists, with an assist credited when a player's pass immediately leads
arXiv:2610.12694v1 Announce Type: new Abstract: Molecular machine learning evaluates out-of-distribution performance with structure disjoint splits, a construction rule fixed once at the scale its lib
deepagents just hit 30k stars on github! deepagents is great for building agents that do complex work. they manage context well and use a durable runtime. though inspired by coding agent design, deepa
Enterprise AI scalability is running into a hard budget wall for some customers. As agentic workloads multiply, cloud token bills are consuming allocations faster than planned, prompting companies to
arXiv:2507.19608v2 Announce Type: replace Abstract: On-device LLM inference is increasingly important for edge platforms but remains challenging due to high computational and memory demands and tight
arXiv:2610.13406v1 Announce Type: cross Abstract: Forecasting desertification has received far less attention than mapping it. We use a convolutional LSTM (ConvLSTM) trained on ten annual Earth Observ
arXiv:2610.12637v1 Announce Type: new Abstract: We consider hole closure in a planar multi-agent system whose sensing disks form a time-varying Cech complex. We propose a harmonic-covariance feedback
arXiv:2610.12774v1 Announce Type: cross Abstract: Autonomous small-body proximity operations require continuous-thrust guidance under uncertain gravity, solar-radiation pressure (SRP), and stochastic
arXiv:2502.11864v2 Announce Type: replace-cross Abstract: Agents in real-world scenarios like automated driving deal with uncertainty in their environment, in particular due to perceptual uncertainty.
arXiv:2610.13262v1 Announce Type: new Abstract: Memory-dependent manipulation requires a policy to track execution state and recover visual evidence that is no longer observable. We propose dual-strea
arXiv:2610.13599v1 Announce Type: new Abstract: Diagnostic information in multi-view medical imaging studies, like echocardiography, is distributed across views, each capturing different aspects of ca
arXiv:2610.12507v1 Announce Type: cross Abstract: Sensing-aided beam prediction can reduce the beam-training overhead of millimeter-wave (mmWave) systems by leveraging environmental information from c
arXiv:2610.12541v1 Announce Type: new Abstract: Boundary-value problems for the Laplace equation develop singular behaviour near corners, edges and junctions that smooth approximators resolve poorly.
arXiv:2610.13013v1 Announce Type: new Abstract: Softmax-based multimodal emotion recognition methods often assign high confidence even when sensor data are corrupted or contradictory, for example when
arXiv:2610.13345v1 Announce Type: new Abstract: Existing real-world reinforcement learning methods improve robot policies by combining human corrections with autonomous rollouts. However, accumulated
arXiv:2601.13600v2 Announce Type: replace Abstract: NLP systems increasingly aggregate claims from retrieved passages, documents, and generated reasoning steps. Yet current factuality methods mostly v
arXiv:2610.13923v1 Announce Type: cross Abstract: Deep-space communications operate under intermittent connectivity, long propagation delays, and relay storage constraints. In such networks, the Bundl
arXiv:2505.11304v4 Announce Type: replace-cross Abstract: Federated learning (FL) commonly involves clients with diverse communication and computational capabilities. Such heterogeneity can significan
arXiv:2610.13236v1 Announce Type: cross Abstract: Recent advances have significantly improved the performance of Abstract Meaning Representation (AMR) parsers, yet determining when their outputs can b
If you’re a researcher, please consider sharing your RL environments openly! Something you built for one experiment could help the entire field move forward. I know we’re in dark days for sharing from
arXiv:2610.12631v1 Announce Type: new Abstract: Recently, soft robotic procedures are being developed aiming at achieving targeted minimally invasive operations or drug administration in specific loca
arXiv:2410.03043v3 Announce Type: replace Abstract: Current research on deep machine unlearning primarily focuses on improving or evaluating the overall effectiveness of unlearning methods while overl
arXiv:2610.13574v1 Announce Type: new Abstract: Feature selection is a central problem in high-dimensional financial regression, where large numbers of engineered variables and strong correlations amo
https://preview.redd.it/3ekngxk224vh1.png?width=1080&format=png&auto=webp&s=9bfe5c92033e17d5b2fb4529f1320c99455a138b I built a GPU compiler and wrote an article about it, focusing on concepts shared b
arXiv:2610.13158v1 Announce Type: new Abstract: Reactive collision avoidance in unknown, cluttered environments must perceive obstacles and correct motion within milliseconds. Existing methods rely on
arXiv:2610.13028v1 Announce Type: new Abstract: Neural operators that learn physical laws from data should generalize beyond their training distribution and expose the learned law in closed form. The
arXiv:2610.13717v1 Announce Type: new Abstract: Federated clustering can support applications such as patient stratification across hospitals and customer segmentation across distributed financial dat
Meta AI Research: Meta introduces Muse Wonder and Muse Wonder Full, saying they deliver state-of-the-art performance on personal and professional agentic tasks — Fourteen months ago, we began a ground
https://preview.redd.it/f7ytj63103vh1.jpg?width=2996&format=pjpg&auto=webp&s=4f5ff97fae270d5b912fcb4193dd75b865604dce Since my last post has been deleted unfortunately (due to a mega-link), here we go
arXiv:2510.00375v3 Announce Type: replace Abstract: While adaptive experimental design has outgrown one-dimensional, staircase-based adaptations, most cognitive experiments still control a single fact
arXiv:2610.13674v1 Announce Type: cross Abstract: Linearizing softmax attention offers a route to efficient Transformer inference, but preserving pretrained attention remains challenging. We identify
arXiv:2610.12985v1 Announce Type: cross Abstract: Neural-network variational Monte Carlo provides an accurate route to solving the electronic Schrodinger equation, but many neural wavefunctions are op
arXiv:2610.13871v1 Announce Type: new Abstract: Many optimization problems provide direct access to only part of the gradient, while the remaining component must be inferred from function evaluations.
arXiv:2610.13373v1 Announce Type: new Abstract: Translating language into humanoid motion requires coordinating body parts, determining motion duration, and producing references suitable for robot exe
arXiv:2610.13190v1 Announce Type: cross Abstract: Autonomous landing of unmanned aerial vehicle (UAV) on unmanned surface vehicle (USV) is difficult in high sea states. Existing hierarchical landing m
arXiv:2610.13881v1 Announce Type: new Abstract: A memory that reproduces every current prediction may still have forgotten how to learn from the next observation. We characterize this distinction for