Search: “safety”

This past December, we ran our first fundraiser in six years, setting an ambitious goal of 6M. We ended up receiving a total of 1.8M from small donors and 1.6M in matching from the Survival and Flouri

arXiv:2606.07399v1 Announce Type: cross Abstract: Generative models for counterfactual outcomes have great potential to support decision-making under complex interventions, but existing approaches are

arXiv:2606.07113v1 Announce Type: new Abstract: Large language models are rapidly becoming infrastructural components in high-stakes institutional settings, including public administration, legal reas

arXiv:2606.06903v1 Announce Type: cross Abstract: Human image animation aims to generate a video from a static reference image, guided by pose information extracted from a driving video. Existing appr

arXiv:2606.07068v1 Announce Type: new Abstract: Background: Since 1990 many feature selection methods have been proposed across heterogeneous applications. To validate the usefulness of a new method,

arXiv:2606.06813v1 Announce Type: cross Abstract: Recent text-to-image models built on large-scale Transformer backbones and flow-based objectives deliver strong text-image alignment and high visual q

arXiv:2606.06646v1 Announce Type: cross Abstract: Formalizing complex reasoning from natural text is one of the central challenges in computational linguistics. It requires systems to understand not j

arXiv:2601.05675v2 Announce Type: replace Abstract: Hybrid action space, which combines discrete choices and continuous parameters, is prevalent in domains such as robot control and game AI. However,

arXiv:2503.03660v4 Announce Type: replace Abstract: We introduce a sequence-conditioned critic for Soft Actor-Critic (SAC) that models trajectory context with a lightweight Transformer and trains on a

arXiv:2606.07107v1 Announce Type: new Abstract: Most vision-language-action (VLA) models map observations directly to actions without explicit intermediate planning, which limits performance on long-h

arXiv:2606.07145v1 Announce Type: new Abstract: Text-guided diffusion models have become effective tools for real-image visual editing, where the edited image must follow a target instruction while pr

arXiv:2606.07382v1 Announce Type: new Abstract: We recast classical shrinkage of high-dimensional covariance estimators as empirical risk minimization over a parametric stochastic interpolant between

arXiv:2606.06712v1 Announce Type: cross Abstract: We study the transformation of autoregressive models (ARLMs) into diffusion language models (DLMs). Rather than pretraining from scratch, prior work r

arXiv:2606.07226v1 Announce Type: cross Abstract: Human creativity has emerged as a critical competency in the era of large language models. Assessing creativity in complex, open-ended environments is

arXiv:2606.06555v1 Announce Type: cross Abstract: Noisy evolution strategies under fixed evaluation budgets face a depth-fidelity trade-off: spending evaluations to denoise intra-generation rankings r

arXiv:2606.06514v1 Announce Type: new Abstract: Machine learning systems deployed in high stakes socioeconomic settings routinely display bias. We formalize bias as a symmetry breaking operation: a cl

arXiv:2606.06942v1 Announce Type: cross Abstract: Policymakers in defence and defence-aligned sectors must monitor rapidly evolving research alongside sector priorities relevant to operational and str

arXiv:2505.23131v2 Announce Type: replace Abstract: We study the problem of assigning operations in a dataflow graph to devices to minimize execution time in a work-conserving system, with emphasis on

arXiv:2606.06546v1 Announce Type: new Abstract: Evaluating large language models (LLMs) for education requires measuring how models teach, not only what they know. Existing benchmarks emphasize domain

arXiv:2606.06785v1 Announce Type: cross Abstract: We study finite-sample change detection for one-dimensional noisy dynamical systems using partition-based empirical approximations of stationary behav

arXiv:2505.14289v2 Announce Type: replace Abstract: Graphical User Interface (GUI) agents powered by Multimodal Large Language Models (MLLMs) are increasingly deployed yet vulnerable to Environmental

arXiv:2603.22327v2 Announce Type: replace-cross Abstract: Systematic literature reviews (SLRs) are a demanding and high-stakes form of scientific knowledge synthesis that remains underspecified as an

arXiv:2606.06871v1 Announce Type: new Abstract: Diagnosing 802.11 packet captures requires expert protocol knowledge, is slow, inconsistent across engineers, and unscalable. LLM-based approaches sound

arXiv:2606.07130v1 Announce Type: new Abstract: As AI systems become more widely adopted, the demand for factual and faithful generation grows. Properly attributing information through citations becom

arXiv:2606.06547v1 Announce Type: cross Abstract: Diffusion Large Language Models (dLLMs) refine tokens iteratively but commit them irreversibly, leading to a 'stability lag' where early decisions rem

arXiv:2606.05967v2 Announce Type: replace-cross Abstract: In this paper, we study the finite-time behavior of the TD(0) temporal-difference method with linear function approximation (LFA). We consider

arXiv:2606.06615v1 Announce Type: cross Abstract: Retrieving music using natural language descriptions has improved with contrastive audio-text models such as CLAP, but current systems remain limited

arXiv:2606.07034v1 Announce Type: new Abstract: AI-generated image detectors achieve high accuracy on in-distribution data but often fail on unseen generators. A key obstacle to understanding this fai

arXiv:2606.06885v1 Announce Type: cross Abstract: Human Image Animation has seen significant advancements, primarily driven by diffusion models. However, existing methods typically demand substantial

further evidence that people shoveling money into AI are either bad at math or blind to risk Striking paper from Wharton. The big conclusion: AI must increase productivity 2.7x -- and quickly -- or te

Gary Marcus argues that large language models based on transformers quickly reach their limitations, prompting developers to add external tools as workarounds, while neurosymbolic AI—which combines ne

arXiv:2606.07400v1 Announce Type: new Abstract: Many scientific problems require inferring unobserved mechanistic latent states from indirect observations. While classical approaches, including expect

arXiv:2606.06572v1 Announce Type: cross Abstract: We argue that modern generative models create structural risks for knowledge and cultural production at current, sub-AGI capability levels. We define

arXiv:2606.06967v1 Announce Type: new Abstract: Generative policies provide expressive and multimodal action distributions, making them attractive for reinforcement learning (RL) in complex continuous

arXiv:2606.06892v1 Announce Type: new Abstract: Scalable data attribution methods typically assign isolated utility scores to individual training examples. This prevalent additive assumption fundament

arXiv:2606.06986v1 Announce Type: new Abstract: While green finance has become a key instrument for low-carbon city transitions, its actual decarbonization effects and transmission mechanisms remain u

Historic: when the President of the United States can’t provide a single bit of specific concrete evidence to back up his serious charges, and has a temper tantrum when pressed. Trump has a meltdown a

arXiv:2606.07515v1 Announce Type: cross Abstract: We investigate the probabilistic reasoning capabilities of large language models through a controlled benchmarking study on discrete probability probl

Hypers got hype but this is an embarrassingly bad piece of analysis that sets up a false dichotomy and ignores the fact that Terence Tao also signed the Leiden Declaration. 🤦‍♂️ This post is unavailab

Gary Marcus, a prominent AI researcher and critic, is considering writing a book titled 'Seven Lies About AI' that would debunk common misconceptions about artificial intelligence, with a planned sequ

i expect value for money to increase over time as competitive pressures force providers to lower prices. but in the short time, looks like the opposite may be happening: Does a token buy you more or l

🤣 I have to think that anyone who buys the SpaceX IPO just isn’t that good at math. Or history. “Garnering that almost 600x increase means hiking sales 50% a year, on average, for a decade.” 👇🏼 https:

I will start to take Geoff Hinton seriously again (I used to and don’t anymore) when - radiologists actually start losing jobs - he acknowledges that LLMs do sometimes effectively memorize things - he

I would trust @eastdakota over Vinod Khosla any day of the week; it’s not even close. One is a man of integrity, with compassion for other human beings; the other isn’t. Uhhh… your memory is failing,

in hindsight, this was chump change New: Microsoft and OpenAI plotting new 'Stargate' supercomputer that could cost $100 billion. An incredible look at what it will take to build the next generation o

arXiv:2606.06857v1 Announce Type: new Abstract: A central goal of cognitive neuroscience is to characterize the features that are represented by human language cortex. Artificial language models (LMs)