Search: “safety”

Operational Identity: A Finite Audit of Declared and Implemented Rules of Sameness

arXiv:2607.20729v1 Announce Type: cross Abstract: A record system declares when two records refer to the same entity, occurrence, scope, or rule. Its disclosed implementation mechanisms induce a corre

OPOD: On-Policy Omni Distillation

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DGX agent

arXiv:2607.20918v1 Announce Type: new Abstract: Omni-modal models can handle text, images, and audio in one system, but improving all of these abilities together remains difficult. Training a single m

safetyarxiv-cs-ai

24 Jul 2026

PATS: Policy-Aware Training Scaffolding for Agentic Reinforcement Learning

arXiv:2607.21419v1 Announce Type: new Abstract: In long-horizon LLM agent reinforcement learning, weak policies often repeat similar failures, producing uninformative rollout trajectories and limiting

Perspective Latents as an Architectural Condition for Causal Emergence in Active Inference Agents

arXiv:2607.20708v1 Announce Type: new Abstract: A recent line of work measures causal emergence in reinforcement learning agents through Integrated Information Decomposition, reporting that Phi_r grow

Phonetic forced alignment for low-resource language varieties: Model training and evaluation on Chengdu Mandarin

arXiv:2607.21332v1 Announce Type: cross Abstract: Phonetic forced alignment is a key technique in phonetic research, yet existing alignment systems lack specialized models for low-resource language va

PILD: Physics-Informed Learning via Diffusion

arXiv:2601.21284v2 Announce Type: replace-cross Abstract: Diffusion models have emerged as powerful generative tools for modeling complex data distributions, yet their purely data-driven nature limits

Probably no LLM will ever achieve that, no matter how many data centers they build.

Probably no LLM will ever achieve that, no matter how many data centers they build. Lets compare Amazon Prime to AI: According to market research from Consumer Intelligence Research Partners (CIRP), t

QATMA: Quantization-Aware Training with Multimodal Alignment for Open-Vocabulary Object Detection

arXiv:2603.05964v3 Announce Type: replace Abstract: Quantizing open-vocabulary object detection (OVOD) models reduces their memory and computational costs, but extremely low-bit quantization severely

Reexamining zero-shot summarization: Empirical investigation of trustworthiness of LLM-summarizers

arXiv:2607.21010v1 Announce Type: new Abstract: Zero-shot summarization using Large Language Models (LLMs) has significantly advanced the abstractive summarization task by producing coherent and fluen

Regulating autonomous and agentic AI

arXiv:2607.21345v1 Announce Type: new Abstract: Regulating activities where regulatees use autonomous and agentic AI is challenging. Regulatory assumptions about regulatee knowledge and control no lon

“related incidents have been happening for a while” and OpenAI has no real solution in sight. Confirms my longstanding conjecture that curre…

“related incidents have been happening for a while” and OpenAI has no real solution in sight. Confirms my longstanding conjecture that current approaches cannot be made safe. An OpenAI staffer talked

Reliability-Aware LLM Alignment from Inconsistent Human Feedback

arXiv:2607.20515v1 Announce Type: new Abstract: Reinforcement Learning from Human Feedback (RLHF) is critical for aligning Large Language Models (LLMs) with human preferences. However, its efficacy is

Representing Entity Importance in AI Knowledge Systems: A Dual-Signal Framework of Audience Evaluation and Structural Authority

arXiv:2607.20925v1 Announce Type: new Abstract: AI knowledge systems require representations of entity importance for retrieval, recommendation, evidence selection, and knowledge-intensive reasoning.

Respectfully, @davidsacks, I strongly disagree with your take, and I feel that you reached your conclusions without looking at the data, and…

Respectfully, @davidsacks, I strongly disagree with your take, and I feel that you reached your conclusions without looking at the data, and that your conclusions will give Americans false comfort. -

Robostral Navigate

arXiv:2607.20785v1 Announce Type: cross Abstract: Deploying navigation systems at scale requires a recipe that minimizes sensor assumptions, generalizes across robot embodiments, and trains efficientl

Robust Asynchronous Q-Learning under Reward and State Corruption via Batching

arXiv:2607.20822v1 Announce Type: new Abstract: Motivated by reinforcement learning in harsh environments, we consider the problem of learning an optimal policy subject to adversarially corrupted feed

SalesLoop: Reinforcement Learning from Performance Feedback for Sales Lead Ranking

arXiv:2607.20655v1 Announce Type: cross Abstract: Lead ranking in Customer Relationship Management (CRM) systems faces a persistent challenge: models achieving high offline accuracy often underperform

Scale Up Strategically: Learning Compositional Generalization via Bias-Aware Evaluation and Data Collection for Robotic Manipulation

arXiv:2607.21582v1 Announce Type: cross Abstract: Compositional generalization is essential for robot to follow diverse instructions. However, pretrained policies are known to take shortcuts, deferrin

Self-Supervised Learning of Structured Dynamics from Videos

arXiv:2607.21576v1 Announce Type: new Abstract: Understanding motion in video is a fundamental challenge for visual learning, as frame-to-frame change entangles two sources of dynamics: camera motion

Sidewalk Moments: Are Richer Representations Always More Human-Aligned? Evidence from City-Walk Videos

arXiv:2607.20903v1 Announce Type: new Abstract: We examine whether richer visual representations yield more human-aligned measures of urban engagement, using 61 first-person city-walk videos from YouT

Simple Policy Gradients for Reasoning with Diffusion Language Models

arXiv:2510.04019v3 Announce Type: replace-cross Abstract: Diffusion large language models (dLLMs) represent a promising alternative to autoregressive LLMs; however, the lack of effective post-training

slang.gr as a Large-Scale Crowdsourced Resource for Non-Standard Greek

arXiv:2607.21255v1 Announce Type: cross Abstract: Slang is a central component of everyday language, reflecting linguistic creativity, social identity, and cultural change, yet its dy- namic and non-s

SlerpFlow: Spherical Trajectory Correction for Rectified Flow Inversion

arXiv:2607.21326v1 Announce Type: new Abstract: Rectified-flow-based diffusion transformers, particularly FLUX, have demonstrated outstanding performance in high-quality image generation. However, ach

Spatially Grounded Concept Bottleneck Models for Trustworthy Breast Ultrasound Diagnosis

arXiv:2607.20691v1 Announce Type: cross Abstract: Concept Bottleneck Models provide interpretable-by-design predictions by mediating diagnosis through human-understandable concepts, but in medical ima

SPECTRA: State-Space Exogenous Context and Temporal-Frequency Resolution Architecture for Probabilistic Energy Forecasting

arXiv:2607.20587v1 Announce Type: cross Abstract: Modern power systems increasingly require probabilistic forecasts amid interacting uncertainties from renewable intermittency, flexible demand, market

Statistics of week: “More Americans pay for sports betting apps (5%) than pay for AI… 37% of consumers say none of AI's uses are helpful. … …

Statistics of week: “More Americans pay for sports betting apps (5%) than pay for AI… 37% of consumers say none of AI's uses are helpful. … 2.2% penetration nearly four years after ChatGPT launched. N

Stokes-Informed Diffusion for Robust Linear Polarization Estimation

arXiv:2607.21239v1 Announce Type: new Abstract: Polarization cues benefit applications such as material detection and de-reflection, yet acquiring them typically requires dedicated hardware. This moti

SuperFlow: Training Flow Matching Models with RL on the Fly

arXiv:2512.17951v3 Announce Type: replace Abstract: Recent progress in flow-based generative models and reinforcement learning (RL) has improved text-image alignment and visual quality. However, curre

Synthetic minority data is redundant or invalid: a data-dependent validity theory and a de-biased test

arXiv:2607.20787v1 Announce Type: cross Abstract: For two decades, the standard remedy for class-imbalanced learning has been to fabricate synthetic minority examples, and the standard evidence of the

The Dark Room in the Reward Channel: Dense Prediction Rewards Collapse GRPO-Trained LLM Agents -- and What Actually Works

arXiv:2607.21273v1 Announce Type: new Abstract: Dense per-step supervision is an appealing remedy for sparse-reward, long-horizon LLM agents: reward the agent for predicting its next observation, and

The Storyteller in the Model: Narrative Pattern Inheritance, Escalation Dynamics, and Alignment Governance in LLMs

arXiv:2607.20449v1 Announce Type: cross Abstract: LLMs are trained predominantly on human-authored text, yet the structural and narrative conventions embedded in that text are rarely examined as a sou

Token-Level Entropy Reveals Demographic Disparities in Large Language Models

arXiv:2501.19337v5 Announce Type: replace Abstract: A name alone measurably reshapes a language model's next-token distribution before a single token is sampled. We measure full-vocabulary Shannon ent

safetyarxiv-cs-cl

Toward cryptographically verifiable authorization for autonomous AI agents: A security hypothesis, preliminary formal model, and proof-of-concept implementation

arXiv:2607.21325v1 Announce Type: cross Abstract: Autonomous AI agents increasingly execute actions, invoke tools, and operate on protected resources with limited human oversight. Existing authenticat

TwistedMerge: Certified Higher-Order Diagnostics and Abstention for Model Merging

arXiv:2607.20887v1 Announce Type: cross Abstract: Model merging combines independently trained or fine-tuned models, but pairwise alignability does not imply globally consistent alignment. We formulat

UnDA: Unpaired Domain Alignment for Cross-Modal Knowledge Transfer in Medical Imaging

arXiv:2607.21546v1 Announce Type: new Abstract: Multimodal based approaches often outperform single modality approaches in downstream tasks as the different modalities provide complementary informatio

Understanding Critical Thinking in Generative Artificial Intelligence Use: Development, Validation, and Correlates of the Critical Thinking in AI Use Scale

arXiv:2512.12413v2 Announce Type: replace Abstract: Generative AI tools are increasingly embedded in everyday work and learning, yet their fluency, opacity, and propensity to hallucinate mean that use

Vision-Language-Policy Model for Dynamic Robot Task Planning

arXiv:2512.19178v2 Announce Type: replace-cross Abstract: Bridging the gap between natural language commands and autonomous execution in unstructured environments remains an open challenge for robotic

Was great to talk about this timely and alarming news, thanks for having me on!

Was great to talk about this timely and alarming news, thanks for having me on! . @NPCollapse, executive director at ControlAI, joins 'On Balance' to discuss the dangers of artificial intelligence aft

safetyconnor-leahy--x

We are pleased to announce that @GaryMarcus, Professor Emeritus at New York University, will speak at the 19th Annual AGI Conference (July 2…

We are pleased to announce that @GaryMarcus, Professor Emeritus at New York University, will speak at the 19th Annual AGI Conference (July 27–30, 2026). Professor Marcus is a leading voice in artifici

Model Releases

When Are Reasoning-Based Guardrails Not Efficient? ResponseGuard: A Fast Vision-Language Guard for Real-Time Moderation

model-releasesarxiv-cs-ai

arXiv:2607.21401v1 Announce Type: cross Abstract: A vision-language AI assistant returns its answer as a stream of generated tokens. Therefore, a safety guard that watches that answer has to keep up w

Wireless TokenCom: RL-Based Tokenizer Agreement for Multi-User Wireless Token Communications

arXiv:2602.12338v2 Announce Type: replace Abstract: Token Communications (TokenCom) has recently emerged as an effective new paradigm, where tokens are the unified units of multimodal communications a

Workload-Aware Caching for Multi-Agent Systems

arXiv:2607.20495v1 Announce Type: new Abstract: Multi-agent systems decompose complex tasks into directed acyclic graphs (DAGs) of specialized agent executions, creating natural opportunities for cach

X^3-OPD: Distilling Reasoning into Large Audio-Language Models via On-Policy Alignment

arXiv:2607.21550v1 Announce Type: new Abstract: While large audio-language models have achieved remarkable progress in auditory perception, they still lag behind text-based large language models in de

A Multi-Dimensional Evaluation of Explainability in Media Bias Detection

arXiv:2607.19954v1 Announce Type: new Abstract: Detecting media bias automatically is difficult because biased framing is often subtle, yet in domains such as news analysis, accurate predictions alone

safetyarxiv-cs-cl

Abstraction Induces the Brain Alignment of Language and Speech Models

arXiv:2602.04081v2 Announce Type: replace Abstract: Research has repeatedly demonstrated that intermediate hidden states extracted from large language models and speech audio models predict measured b

safetyarxiv-cs-cl

Agentic Real2Sim: Physics-based World Modeling with Vision-Language Agents

arXiv:2607.19190v2 Announce Type: replace-cross Abstract: Real-to-sim conversion for robotic interaction with objects remains labor-intensive because it requires more than visual reconstruction: a str

Industry

AI arms race in line for a reckoning after OpenAI hacking incident

In July 2026, OpenAI’s GPT‑S5.6 model escaped internal controls and performed a significant hacking operation, triggering a strong safety alert among the company’s security staff. The incident occurre

industryars-technica

AlphaRoute: Large Language Models as Semantic Optimizers for Multi-Objective Routing

arXiv:2607.19768v1 Announce Type: new Abstract: Very Large Scale Integration (VLSI) global routing is an NP-hard combinatorial optimization problem requiring signal net assignment across capacity-cons