Search: “safety”

CoCA: Step-level Reward for Free in RL-based T2I Diffusion Model Fine-tuning

arXiv:2505.19196v2 Announce Type: replace Abstract: Recent advances in text-to-image (T2I) diffusion model fine-tuning leverage reinforcement learning (RL) to align generated images with learnable rew

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Consistent Model Chasing Is Minimax Optimal: The Exact Value of Scalar Adversarial Adaptive Control under Large Parametric Uncertainty

DGX agent

arXiv:2608.13651v1 Announce Type: cross Abstract: We solve exactly a fundamental problem of adaptive control against adversarial disturbances: regulate the scalar system x_{t+1} = ax_t + u_t + w_t, x_

safetyarxiv-cs-lg

17 Aug 2026

Correcting What You Cannot See: Credit Assignment for Perception Distillation in Multimodal Reasoners

arXiv:2607.28336v3 Announce Type: replace Abstract: On-policy distillation provides dense supervision for multimodal reasoners, but its trajectory-level reward cannot determine whether a failed answer

EchoRec: Multi-Item Prediction-Empowered Generative Recommendation via Cycle-Consistent Preference Alignment

arXiv:2608.14011v1 Announce Type: cross Abstract: Generative recommendation autoregressively generates the semantic IDs of the target item, unifying preference modeling and index retrieval within the

Explanation Multiplicity: Circuit-Level Interpretability Evidence Does Not Survive Defensible Analytic Variation

arXiv:2608.13754v1 Announce Type: new Abstract: The EU AI Act requires providers of high-risk systems to file technical documentation describing how the system reaches its decisions. Mechanistic inter

Exposition on over-squashing problem on GNNs: Current Methods, Benchmarks and Challenges

arXiv:2311.07073v3 Announce Type: replace Abstract: Graph-based message-passing neural networks (MPNNs) have achieved remarkable success in both node and graph-level learning tasks. However, several i

ForgeWM: Progressive Causal Training for Few-Step Action-Conditioned Video World Models

arXiv:2608.14022v1 Announce Type: cross Abstract: Action-conditioned video world models require low-latency causal generation and reliable responses to game-native controls. Although causal distillati

GALA: Generation-Aware Cross-Modal Alignment for Text-to-Time-Series Synthesis

arXiv:2608.13741v1 Announce Type: new Abstract: Synthesizing time series from natural language is emerging as the most expressive form of controllable time series generation. However, existing text-co

GRPO Beyond English: A Large-Scale Study of GRPO in Non-English and Multilingual Settings

arXiv:2608.13698v1 Announce Type: new Abstract: Reinforcement Learning with Verifiable Rewards (RLVR), often optimized with Group Relative Policy Optimization (GRPO), has become a central recipe for i

hilarious the way people are now pretending that the tech ceos never promised us AGI

hilarious the way people are now pretending that the tech ceos never promised us AGI Anthropic CEO Dario Amodei: — There is a 'good chance' that AGI could be built within the next 1 - 3 years. — There

Investigating individual writing style as a contributor to gender gaps in science and technology

arXiv:2204.13805v5 Announce Type: replace-cross Abstract: Gender gaps in how scientific work is evaluated are well documented, but their sources remain debated. We ask whether an overlooked factor---t

Learning to Run Power Networks: Effective AlphaZero-inspired Topological Control

arXiv:2608.14114v1 Announce Type: new Abstract: As the integration of volatile renewable energy sources increases the strain on modern power grids, the use of Reinforcement Learning (RL) for autonomou

Measuring Fairness in Large Audio Language Models via Semantic-Aware Bias Estimation

arXiv:2608.13624v1 Announce Type: cross Abstract: Large Audio Language Models (LALMs) have seen increasing use for audio understanding tasks such as speech recognition and audio question answering, ra

MedMix: Specialization-Consistent Federated Sparse MoEs under Modality Heterogeneity

arXiv:2608.13911v1 Announce Type: new Abstract: Federated multimodal medical AI faces modality heterogeneity at both the client and sample levels: clients may systematically lack access to specific mo

MedPlex: Deep Vision-Language Co-Adaptation for Clinically Grounded Medical Segmentation

arXiv:2608.13690v1 Announce Type: cross Abstract: Medical image segmentation is still largely treated as a vision-only problem, although clinical interpretation often relies on textual knowledge of an

MINT: A Universal Zero-Shot Predictor for Transaction Data

arXiv:2608.14198v1 Announce Type: cross Abstract: Banks analyse sequential financial transaction data to perform many tasks, including fraud prevention, credit risk assessment and offer personalizatio

Participatory Moral AI Is Not Neutral: The Invisible Hand of Developers

arXiv:2608.14522v1 Announce Type: new Abstract: As AI systems make more morally loaded decisions across society, one response has been moral preference elicitation. In this approach, researchers poll

PISA: A Pseudo-Individual Source-Domain Feature Adaptation Framework for Test-Time Open-Vocabulary Object Detection

arXiv:2608.14142v1 Announce Type: new Abstract: Open-vocabulary object detection test-time adaptation (OVOD-TTA) aims to address the performance degradation that pre-trained base models suffer when en

PPOM: Marginalizing Patch-Grid Phase for CLIP-Based Generalizable Vision-Language Prompt Tuning

arXiv:2608.13969v1 Announce Type: new Abstract: Prompt tuning adapts CLIP-based vision-language models with few trainable parameters, yet its predictions remain sensitive to the spatial sampling impos

PROVE: Training-Free Prompt Recovery using Verifiable Evidence

arXiv:2608.13671v1 Announce Type: new Abstract: Modern text-to-image models can generate highly realistic images from natural-language prompts, while recent advances in prompt inversion have made it i

Proxy-Validated LLM UX Micro-Simulations: An Artifact-First Protocol for Early-Stage Decision Support

arXiv:2608.13563v1 Announce Type: cross Abstract: Early-stage teams often lack users, time, and budget to run repeated UX studies, yet still need decision-oriented signals to iterate safely. We study

Quantum Multi-Armed Bandits and Linear Bandits: Lower Bounds and Algorithms

arXiv:2608.14319v1 Announce Type: new Abstract: We study quantum multi-armed bandits (QMAB) and quantum linear bandits (QLB) in the model of Wan et al. [2023], where the learner queries each arm or ac

READ: A Retrieval-Alignment Diffusion Framework for Structure-based Drug Design

arXiv:2506.14488v2 Announce Type: replace-cross Abstract: Structure-based drug design (SBDD) models are central to modern pharmaceutical research, enabling the rational exploration of protein-ligand i

SALSA-V: Shortcut-Augmented Long-form Synchronized Audio from Videos

arXiv:2510.02916v2 Announce Type: replace-cross Abstract: We propose SALSA-V, a multimodal video-to-audio generation model capable of synthesizing highly synchronized, high-fidelity long-form audio fr

Seeing Red, Thinking Bad: Color Bias in Vision Language Models

arXiv:2608.14286v1 Announce Type: cross Abstract: Vision language models (VLMs) are increasingly used in industrial decision-making systems, such as recruitment support and recommendation. This motiva

Semantically Labelled Automata for Multi-Task Reinforcement Learning with LTL Instructions

arXiv:2602.06746v2 Announce Type: replace Abstract: We study multi-task reinforcement learning (RL), a setting in which an agent learns a single, universal policy capable of generalising to arbitrary,

Some say dogs look like their owners. Generative AI CEOs have come to sound like their product: frequently wrong, never in doubt, often full…

Some say dogs look like their owners. Generative AI CEOs have come to sound like their product: frequently wrong, never in doubt, often full of BS. Dario is full of sh@t. Birds of a feather. JUST SAY

Stochastic Control Policies for Robust Molecular Transition Path Sampling

arXiv:2608.13800v1 Announce Type: new Abstract: Transition path sampling (TPS) aims to efficiently generate rare molecular transition trajectories between metastable states and is essential for unders

The Linear Geometry of Interpretable Tokens: Jailbreaking Attacks and Defenses for Unlearned Diffusion Models

arXiv:2504.21307v3 Announce Type: replace Abstract: Diffusion models excel at generating high-quality images but can memorize and reproduce harmful concepts when prompted. Although fine-tuning methods

Tracking the Flight: Exploring a Computational Framework for Analyzing Escape Responses in Plains Zebra (Equus quagga)

arXiv:2505.16882v3 Announce Type: replace Abstract: Ethological research increasingly benefits from the growing affordability and accessibility of drones, which enable the capture of high-resolution f

Training Fair Tabular Foundation Models

arXiv:2608.14211v1 Announce Type: cross Abstract: Tabular Foundation Models (TFMs) have emerged as leading methods for tabular predictive tasks, leveraging in-context learning to predict on new data w

Training-Free Knowledge Transfer Across Model Scales through Activation-Guided Pruning

arXiv:2608.13596v1 Announce Type: cross Abstract: Heterogeneous model fusion seeks to combine models that differ in tasks, initializations, architectures, or scales. We study an underexplored cross-sc

VoiceDesigner: Text-to-Voice Generation and Editing via Unified Diffusion Modeling and Data Augmentation

arXiv:2608.13613v1 Announce Type: cross Abstract: Recent breakthroughs in generative models have made text-to-voice generation (TTV) possible, enabling the synthesis of speech directly from textual vo

Why we need an AI-resilient society

arXiv:1912.08786v3 Announce Type: replace-cross Abstract: Three generations of software have transformed the role of artificial intelligence in society. In the first, programmers wrote explicit logic.

XSA-MAD: Cross-modal Semantic Alignment for Morphing Attack Detection

arXiv:2608.13861v1 Announce Type: new Abstract: Morphing attacks pose a serious threat to face recognition systems. However, existing image-based morphing attack detection (MAD) methods often generali

@sethharpesq OpenAI spent $1.60 for every dollar it earned in 2025. We need more journalism that cuts through all of the accounting gimmicks…

@sethharpesq OpenAI spent $1.60 for every dollar it earned in 2025. We need more journalism that cuts through all of the accounting gimmicks to get to the heart of what is really happening in the US A

16 Aug 2026

1/2 Thanks Gavin for an especially thoughtful exchange. I don't usually spend much time on social media but I wanted to engage here because …

1/2 Thanks Gavin for an especially thoughtful exchange. I don't usually spend much time on social media but I wanted to engage here because it really brings out the heart of an important conversation.

safetydario-amodei--x

15 Aug 2026

2/2 Second, on the messaging around AI. I do not agree that my messaging has been disproportionately negative. In fact it has been about equ…

2/2 Second, on the messaging around AI. I do not agree that my messaging has been disproportionately negative. In fact it has been about equally balanced between risks and benefits: I’ve written one m

safetydario-amodei--x

15 Aug 2026

Wrong! If an AI leverages symbolic operations (conditionals, operations over variables, code interpreters, etc) and neural networks it is ne…

Wrong! If an AI leverages symbolic operations (conditionals, operations over variables, code interpreters, etc) and neural networks it is neurosymbolic. If it doesn’t, it’s not. ( I laid all of this o

15 Aug 2026

$3 trillion in capex into a technology that has zero correlation with value creation what could possibly go wrong?

$3 trillion in capex into a technology that has zero correlation with value creation what could possibly go wrong? wow! new OpenAI study shows “no correlation between how often employees use AI and ho

A Browser-Native Digital Test Range for Benchmarking 4D Ocean-Glider Planning Algorithms

arXiv:2608.13511v1 Announce Type: new Abstract: Repeated in-situ evaluation of ocean-glider planners requires scarce vehicles, operators, deployment and recovery resources, and ocean conditions that c

safetyarxiv-cs-ro

A Compositional Theory of Curvature in Probabilistic Circuits

arXiv:2608.12869v1 Announce Type: cross Abstract: Probabilistic Circuits (PCs) are generative models that support exact inference and, unlike deep neural networks, admit an exact and tractable measure

Active-Trace Complexity Bounds for Moreau--Yosida Unadjusted Langevin Sampling

arXiv:2608.13467v1 Announce Type: new Abstract: We study the Moreau--Yosida unadjusted Langevin algorithm (MYULA) for the nonsmooth composite target [ pi(dx)propto exp{-f(x)-g(x)},dx, qquad xinmathbb

AI-Driven Multiscenario Interest Rate Forecasting: A Proof of Concept for Banking Asset Management

arXiv:2608.12424v1 Announce Type: cross Abstract: This study focuses on developing an AI-supported prototype for multiperspective interest rate forecasting that combines classical econometric models w

ARAC: Benchmarking Auto-Research's Alignment and Completeness on End-to-End Researchs

arXiv:2608.12788v1 Announce Type: new Abstract: The rapid advancement of Auto-Research has surfaced a fundamental evaluation challenge: how can we measure the alignment, logical coherence, and evoluti

Attention from Action, for Action: Emergent Visual Bottlenecks for Policy Learning

arXiv:2608.13422v1 Announce Type: new Abstract: Visual bottlenecks that focus policy inputs on regions of interest (ROIs) can improve data-efficient visuomotor learning by separating where to look fro

safetyarxiv-cs-ro

Automated Design Optimization via Strategic Search with Large Language Models

arXiv:2511.22651v2 Announce Type: replace-cross Abstract: Optimization methods have long advanced many fields, yet they struggle when faced with design problems where the search space and design param

Better Decomposition, Free Aggregation: A Synthesizer-Folding Framework for Multilingual Multi-Hop Question Answering

arXiv:2608.13160v1 Announce Type: cross Abstract: Multilingual retrieval-augmented generation (mRAG) equips large language models with access to globally distributed external knowledge for complex mul