Search: “safety”

MintAct: A Unified Visual Agent for Digital Environments

arXiv:2609.22083v1 Announce Type: new Abstract: We present MintAct, a family of vision-language models that unifies UI grounding, multi-step navigation across mobile, desktop, and web, and visual tool

MIST: Multimodal Survival Prediction with Genomic-Guided Histology Attention

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arXiv:2609.21811v1 Announce Type: new Abstract: Multimodal survival models can combine complementary prognostic information from whole-slide images and genomic profiles, but effective fusion remains c

safetyarxiv-cs-ai

21 Sept 2026

Moral Entropy: Auditing Bias and Uncertainty in Moral Judgment

arXiv:2609.21992v1 Announce Type: new Abstract: Most work in computational ethics treats annotator disagreement on moral content as noise to be voted away, collapsed into majority vote or the more per

MT-WAM: Reorienting the One-Pass Predictive Representation Toward Action Generation

arXiv:2609.21474v1 Announce Type: new Abstract: Fast-WAM shows that video-action co-training improves control without generating future video at inference, making the representation from a single vide

NaViRrator: Robot Navigation from Human-Readable Maps through a Learned Visual Route

arXiv:2609.21316v1 Announce Type: new Abstract: Human-readable maps provide an intuitive interface for specifying robot destinations, but connecting their schematic geometry to egocentric observations

On Repulsive and Attractive Teachers: Separating Correctness from Behavior in Self-Distillation

arXiv:2609.21561v1 Announce Type: cross Abstract: On-policy self-distillation provides dense, token-level supervision by conditioning a model on privileged information and distilling the resulting tea

OneBid: A Unified Auto-Bidding Foundation Model for Diverse oCPX Advertising Scenarios

arXiv:2609.21550v1 Announce Type: cross Abstract: Auto-bidding is central to computational advertising, where strategies must maximize advertisers' conversion value under economic constraints. It has

Outcome-Conditioned End-Effector Geometry Across Vision-Language-Action Policies

arXiv:2609.21659v1 Announce Type: cross Abstract: Vision-language-action (VLA) policies solve the same manipulation task through different action interfaces, but task success alone does not establish

Potential-Field Action Representation for Reinforcement Learning in Contact-Rich Manipulation

arXiv:2609.21609v1 Announce Type: cross Abstract: Model-free reinforcement learning can acquire contact-rich robotic manipulation skills through trial-and-error interaction, but it often requires the

Predictable Failure in Multi-Hop Retrieval: Score-Distributional Confidence Scoring and Abstention

arXiv:2609.22056v1 Announce Type: cross Abstract: Multi-hop retrieval failures are not uniformly distributed across queries: they cluster in structurally predictable subpopulations. We prove two resul

PrismAlign: Prior-Steered Multi-View VLM Alignment for Hallucination-Robust Table OCR

arXiv:2609.21351v1 Announce Type: new Abstract: Table extraction suffers from frequent structural errors and semantic hallucinations. We propose PrismAlign, a multi-VLM framework aligning diverse visu

PSR: Predictive Sensorimotor Representation Learning for Contact-Rich Manipulation

arXiv:2609.21753v1 Announce Type: new Abstract: Contact-rich manipulation requires policies to generate precise actions by reasoning over contact forces, robot configurations, and interaction historie

Rectify, Don't Regret: On-Policy Closed-Loop Training for Multimodal Trajectory Prediction

arXiv:2603.23393v2 Announce Type: replace Abstract: Current trajectory prediction models are primarily trained in an open-loop manner, which often leads to covariate shift and compounding errors when

Recursive Language Models Generalize Out of Domain

arXiv:2609.20831v1 Announce Type: new Abstract: We study when limiting what a language model can see improves learning. We compare standard CoT, the more general learner that reads the full trace, wit

Reinforcement Learning under External Influence: Guarantees, Algorithms, and Sample Complexity

arXiv:2305.16056v5 Announce Type: replace-cross Abstract: In this paper, we study the problem of reinforcement learning under the influence of external events. For this, we consider Markov decision pr

Robust Mixture Models for Algorithmic Fairness Under Latent Heterogeneity

arXiv:2509.17411v2 Announce Type: replace-cross Abstract: Machine learning models optimized for average performance can perform poorly on vulnerable subpopulations. Existing approaches often rely on g

safetyarxiv-cs-lg

SABER: Learning Attention-based Semantic Affordance for Legged Locomotion

arXiv:2609.21572v1 Announce Type: new Abstract: Perceptive legged locomotion has advanced rapidly by integrating terrain geometry into learned policies, yet the integration of terrain meaning remains

Safe Real-Time Policy Steering via Noise-Space Trajectory Optimization for One-Step Generative Policies

arXiv:2609.21220v1 Announce Type: new Abstract: Generative robot policies can represent diverse, multimodal behaviors, but adapting pretrained policies to deployment-time constraints such as collision

Same World, Different Knowledge: When Isolated Audits Misjudge World-Model Repairs

arXiv:2609.21155v1 Announce Type: new Abstract: A repair favored under an isolated input fault can be inferior when deployed modules share the faulty information. We introduce an information-interface

Scaling Forced Alignment to End-User Devices

arXiv:2609.21145v1 Announce Type: new Abstract: The Viterbi algorithm has been previously used to perform forced alignment of audio to text to mine training data from online resources. However, many e

SeeQ: Training Generalist Value Functions for Long-Horizon Robotic Manipulation

arXiv:2609.22085v1 Announce Type: new Abstract: Despite rapid progress, generalist robot policies remain brittle on complex, long-horizon tasks that comprise multiple stages or require repeated attemp

SpaceDiffusion: Over-the-Orbit Diffusion for Space Generate-and-Forward Communications

arXiv:2609.20899v1 Announce Type: cross Abstract: Satellite communications are an essential component of sixth-generation (6G) mobile networks, which provide ubiquitous connectivity for global service

SteganoBackdoor: Evading Data-Poisoning Defenses via Steganographic Backdoors

arXiv:2511.14301v4 Announce Type: replace-cross Abstract: Transformer-based models are highly susceptible to backdoor attacks via supervised fine-tuning (SFT). To red-team existing data-poisoning defe

Talking Past the Machine: Morality, Politeness, and Alignment in Human-AI Dialogue

arXiv:2609.21401v1 Announce Type: cross Abstract: Conversational AI systems produce fluent, socially appropriate responses, yet whether they participate in cooperative communication or merely simulate

The only true alignment seems to be between doomers, hypers and frontier lab founderes, who have converged around a misleading narrative tha…

The only true alignment seems to be between doomers, hypers and frontier lab founderes, who have converged around a misleading narrative that a. completely glosses over the important technical advance

Towards Fine-Grained Object Manipulation: SAM3-Guided Visuomotor Policy with Persistent Memory Learning and Focused Visual Conditioning

arXiv:2609.21621v1 Announce Type: new Abstract: Fine-grained object (FO) manipulation requires robots to distinguish a specified FO from visually similar objects and execute actions reliably despite s

Trajectory Entropy Reinforcement Learning for Robust Robot Motor Skill Learning

arXiv:2505.04193v2 Announce Type: replace Abstract: Simplicity is a critical inductive bias for designing data-driven controllers, especially when robustness is important. Despite the impressive resul

safetyarxiv-cs-lg

ULTRA: Unified Multimodal Control for Autonomous Humanoid Whole-Body Loco-Manipulation

arXiv:2603.03279v2 Announce Type: replace-cross Abstract: Achieving autonomous and versatile whole-body loco-manipulation remains a central barrier to making humanoids practically useful. Yet existing

Visual Proactivity: Enhancing Human-Robot Collaboration Through Intent Communication

arXiv:2609.21729v1 Announce Type: new Abstract: As robots transition from performing repetitive tasks to collaborating with humans, understanding human intent becomes crucial to effective interaction.

Voice-Light: A Full-Duplex Cascaded Voice Agent with Causal Turn-Taking and Speculative Generation

arXiv:2609.20995v1 Announce Type: cross Abstract: Natural spoken interaction requires more than streaming ASR, language generation, and speech synthesis: a system must react to overlap without canceli

We put Grok 4.7 from @SpaceXAI to work on a 2 million insurance claim where one deductible error alone changes the calculation by 143,000.…

We put Grok 4.7 from @SpaceXAI to work on a 2 million insurance claim where one deductible error alone changes the calculation by 143,000. In this Box Agent preview, @grok reconciles the claim against

safetyelon-musk--x

What Should We Ask Next? Retrieval-Aware Question Learning under Partial Evidence

arXiv:2609.21924v1 Announce Type: new Abstract: Interactive retrieval under partial evidence is a sequential information-acquisition problem: an agent must decide which question will create the most u

XCalib Depth-Guided Geometric Optimization for Dense Thermal-Visible Video Registration

arXiv:2609.21770v1 Announce Type: new Abstract: Image registration is a vital preprocessing step in multimodal perception tasks, including image fusion, object detection, and semantic segmentation. In

breaking: author of the study that so many “AI influencers” are taking as evidence that LLMs feel pain tells me “we don’t claim they feel pa…

breaking: author of the study that so many “AI influencers” are taking as evidence that LLMs feel pain tells me “we don’t claim they feel pain.” The good news is that the author understands correctly

excellent thread on that “pain” paper

excellent thread on that “pain” paper 1/ This new preprint on 'pain representation' in LLMs, from @camhberg and colleagues, is getting a LOT of attention - mainly from folks who take it as evidence su

lNot only is this “no moat” regime literally what I predicted in August 2023 but China maybe seems to be understanding the full implications…

lNot only is this “no moat” regime literally what I predicted in August 2023 but China maybe seems to be understanding the full implications of that faster. (Perhaps informed by their painful housing

sure, Trump doesn’t want to regulate AI. except when wants to send people to jail for their models.

sure, Trump doesn’t want to regulate AI. except when wants to send people to jail for their models. Woah… a new report on Anthropic vs. White House negotiations over Fable says things got so heated th

the hidden opportunity cost of this insane bet on generative AI is immense

the hidden opportunity cost of this insane bet on generative AI is immense Economic activity flowing into the AI sector is crowding out other forms of investment. Shalom Lappin, drawing on Robert Gord

caution: @DavidSacks is getting loads of traffic saying the best defense against cyberattacks is more AI. but sometimes that actually makes …

caution: @DavidSacks is getting loads of traffic saying the best defense against cyberattacks is more AI. but sometimes that actually makes things worse, this thread/demonstration from @HeidyKhlaaf sh

even worse, let’s not forget that Hinton made up the quote

even worse, let’s not forget that Hinton made up the quote A few years ago Geoffrey was telling everyone that transformers produce emergent properties then paper after paper came out proving that tran

fuck you, from humanity, to the four selfish twits who filed this lawsuit. and i mean that from the bottom of my heart.

fuck you, from humanity, to the four selfish twits who filed this lawsuit. and i mean that from the bottom of my heart. A new lawsuit claims that Anthropic, OpenAI, SpaceXAI and Google illegally agree

slowdown? what slowdown?

slowdown? what slowdown? Sources: Anthropic considers releasing a new AI model to counter OpenAI's momentum since Astra's launch, ahead of an IPO and after Amodei's call for a slowdown (Reuters) (Visi

Sometimes everybody is right! Me, spring 2023 onwards: giving LLM-driven agents unrestricted internet access with read/write permissions is …

Sometimes everybody is right! Me, spring 2023 onwards: giving LLM-driven agents unrestricted internet access with read/write permissions is going to be a security nightmare. The AI industry: Agents ar

The simple linear trend that will destroy both OpenAI and Anthropic (even as total spend is increasing).

Gary Marcus warns that a simple linear trend—despite growing overall AI spending—will undermine both OpenAI and Anthropic by eroding expected returns and scaling challenges. He argues that this trajec

wait, wasn’t that literally already part of David Sack’s title?

wait, wasn’t that literally already part of David Sack’s title? President Trump announced the formation of the US AI Force to oversee the development of artificial intelligence, and in the near future

weirdly the New York Post (which did that stupid and egregious hatchet job on METR) may well be right about this one

weirdly the New York Post (which did that stupid and egregious hatchet job on METR) may well be right about this one OpenAI and Anthropic oversold AI security breaches to pressure feds into protecting

A Cross-Lingual Acoustic Disease-Alignment Framework for Respiratory Health Assessment from Spontaneous Speech

arXiv:2609.19398v1 Announce Type: cross Abstract: Spontaneous speech offers a scalable, noninvasive signal for respiratory health assessment, yet interpretable models that generalize across languages

18 Sept 2026

A Policy Profile for Croissant: Refusal as a Property of the Dataset