Search: “safety”

Cross-Lingual Alignment Without Joint Training: Do Monolingual Language Models Converge on Universal Representations?

arXiv:2608.27115v1 Announce Type: new Abstract: Cross-lingual alignment in multilingual language models is typically attributed to joint training: shared parameters, mixed-language batches, or explici

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Decoupling Planning and Control for Instructable Agents

DGX agent

arXiv:2608.26788v1 Announce Type: new Abstract: Recent work shows that pre-trained, instruction-tuned vision-language models (VLMs) perform well at mapping from instructions and observations to high-l

safetyarxiv-cs-ai

28 Aug 2026

Difference-in-Differences on a Censored Rating Scale Can Manufacture an Effect: Evidence from a Pre-Registered LLM-Judge Audit

arXiv:2608.27309v1 Announce Type: cross Abstract: Audits of LLM judges certify a bias by contrasting matched conditions, and the strongest designs difference twice: a within-item contrast between two

Disentangling Optimization Scale from Preference Scale in DPO

arXiv:2608.27032v1 Announce Type: new Abstract: Direct Preference Optimization (DPO) is a widely used objective for aligning language models from preference data, with the coefficient eta commonly int

DPA-I2P: Depth-Guided Projective Alignment for Image-to-Point-Cloud Registration in Autonomous Driving

arXiv:2608.26589v1 Announce Type: new Abstract: Image-to-Point Cloud Registration aims to estimate the camera pose of a given image within a 3D scene point cloud, which is a fundamental task in autono

Emotional Preferences as Goal-Priority Regulation

arXiv:2608.27072v1 Announce Type: cross Abstract: A core question in decision-making for agents is whether the relative priorities of competing lower-level objectives can be determined by emotional pr

Evaluator-Dependent Patient-Adaptive ECG Lead-Channel Allocation

arXiv:2608.26827v1 Announce Type: new Abstract: Patient-conditioned acquisition policies for ECG lead-channel selection can outperform population-wide fixed protocols by tailoring the channel budget t

Five Primitives for Governing Autonomous AI Agents at Runtime

arXiv:2608.26696v1 Announce Type: new Abstract: Enterprise deployments of autonomous AI agents inherit a control model built for human users and long-lived services, and the fit fails in three specifi

FLARE: A Failure-Aware Framework for Autonomous Correction and Recovery in Visual-Language Robotic Manipulation

arXiv:2608.26645v1 Announce Type: new Abstract: Vision-Language-Action Models~(VLAs) have demonstrated significant promise in generalizing to complex, long-horizon robotic manipulation tasks. However,

safetyarxiv-cs-ro

Gary and I co-wrote this piece about the security standards we should expect from the AI labs. It’s our attempt to bring some clarity to the…

Gary and I co-wrote this piece about the security standards we should expect from the AI labs. It’s our attempt to bring some clarity to the OpenAI Hugging Face incident. Now live (and free) at Marcus

safetygary-marcus--x

GeoMAD: Geometry-Aware Multi-View Anomaly Detection via Deformable Fusion and Distributional Alignment

arXiv:2608.26724v1 Announce Type: new Abstract: Multi-view anomaly detection (MvAD) detects defects by exploiting complementary observations from multiple camera viewpoints. The central challenge is t

GRAFT: Grounded and Efficient Online Reinforcement Adaptation for Fine-Grained Robot Manipulation

arXiv:2608.27079v1 Announce Type: new Abstract: Pretrained vision-language-action (VLA) policies provide strong priors for robot manipulation, yet adapting them online to fine-grained biomedical tasks

safetyarxiv-cs-ro

GRAS: Guided Reduced-Variance Proposals and Adaptive Selection for Training-Free Reward Alignment in Discrete Diffusion

arXiv:2608.26585v1 Announce Type: new Abstract: Discrete diffusion models have become a strong, widely adopted class of generators for sequence data, and steering them toward a downstream reward at in

Gromov-Monge Flow Matching for Equivariant Graph Generation

arXiv:2608.26961v1 Announce Type: new Abstract: Graphs are invariant under node permutations, motivating the use of permutation-equivariant architectures in generative models. In flow matching, howeve

Incremental Recommendation via Causal Models

arXiv:2608.26804v1 Announce Type: cross Abstract: Recommendation impressions are a finite resource, hence delivering a recommendation to a user who would discover the content organically yields no inc

Instruction Quality Matters: Refining Instructions for Effective Preference Learning

arXiv:2608.26779v1 Announce Type: new Abstract: Preference learning optimizes models using response pairs, yet the informativeness of these pairs is fundamentally shaped by the instructions from which

Interpretable, Fairly Evaluated Automated L2 Speaking Assessment that Beats the Single-Human Ceiling and Why Pause Encoding Does Not Change LLM Fluency Scores

arXiv:2608.26137v1 Announce Type: new Abstract: Second-language (L2) English learners can rarely rehearse speaking with a partner. Speaking is also the most anxiety-laden skill. These gaps drive a fas

ITL: Interpretable Document Alignment with Structured Reference Frameworks

arXiv:2608.27031v1 Announce Type: new Abstract: Measuring alignment between documents and structured reference frameworks requires identifying conceptual evidence distributed throughout the text and r

just had a quick look at microduck_rl the codebase is very elegant, i’d recommend reading the agent.md since it contains quite a few fun qui…

just had a quick look at microduck_rl the codebase is very elegant, i’d recommend reading the agent.md since it contains quite a few fun quirks for reward modeling like head tracking too tight impairs

safetyclem-delangue--x

LAAF: A Layered Accountability Architecture Framework for LLM Applications

arXiv:2608.27102v1 Announce Type: new Abstract: Large Language Models (LLMs) operate in hospitals, courtrooms, banks, and public service desks, where fluent, confident outputs are treated as authorita

Learning-Augmented Online Allocation under Unreliable Advice: Robustness, Exposure Fairness, and Distribution Shift

arXiv:2608.26889v1 Announce Type: new Abstract: Learning-augmented algorithms improve online decisions using predictions, but unreliable advice may harm efficiency and fairness. We study an online all

Learning Woody Clearing With Loss Alignment for Zero-Shot Regrowth and Woody Segmentation

arXiv:2608.26489v1 Announce Type: new Abstract: Detecting woody clearing is vital for managing biodiversity. Deep learning models can detect change in woody vegetation from bitemporal remote sensing i

Making Latent Evolution Explicit: Operator-Structured Transitions for World Action Models

arXiv:2608.27259v1 Announce Type: new Abstract: World Action Models (WAMs) augment robot policies by predicting how task-relevant scene states may evolve under interaction. Recent WAMs increasingly pe

MedFG-VQA: Low-Frequency Memory and Graph Attention for Lightweight Medical VQA

arXiv:2608.26848v1 Announce Type: cross Abstract: Medical Visual Question Answering (Med-VQA) holds significant promise for clinical decision support, yet faces challenges due to limited annotated dat

MENTOR: Reinforcement Learning via Flexible Teacher-Optimized Rewards for Tool-Use Distillation

arXiv:2510.18383v4 Announce Type: replace-cross Abstract: Distilling the tool-use capabilities of large language models (LLMs) into small language models (SLMs) is essential for their practical applic

Mitigating Fabrication in Multi-Stage LLM Pipelines for Hiring: An Empirical Evaluation of Prompt Guardrails and Human-in-the-Loop Checkpoints

arXiv:2608.26171v1 Announce Type: cross Abstract: Multi-stage LLM hiring pipelines (resume improvement, interview question generation, answer feedback) can fabricate credentials, inflate qualifiers, a

MODIS: Multi-Omics Data Integration for Small and unpaired datasets

arXiv:2503.18856v3 Announce Type: replace Abstract: An important objective in computational biology is the efficient integration of multi-omics data. The task of integration comes with challenges: mul

Mutual Debiasing via Dual-Seed Comparison for Probabilistic Sampling in Large Language Models

arXiv:2608.26161v1 Announce Type: cross Abstract: Although Large Language Models (LLMs) demonstrate remarkable capabilities in reasoning and decision-making, high-fidelity probabilistic sampling remai

Now live (and free) at Marcus on AI: takeways on the OpenAI / Hugging Face attack, coauthored with @ZackKorman, focusing not so much on what…

Now live (and free) at Marcus on AI: takeways on the OpenAI / Hugging Face attack, coauthored with @ZackKorman, focusing not so much on what the AI did as on what OpenAI should have done. https://gary

safetygary-marcus--x

PailitaoGR: Latent Think-with-Images for Generative Image Retrieval

arXiv:2608.26658v1 Announce Type: cross Abstract: Generative retrieval has demonstrated strong performance by directly generating product semantic identifiers (SIDs). Extending this paradigm to image

Predicting Consequences and Reinforcing Navigation Policies with Latent World Models

arXiv:2608.26190v1 Announce Type: new Abstract: World models enable agents to reason about future outcomes and learn policies from their knowledge of state transition, but existing approaches primaril

Preserving General Capabilities during Domain Specialization with Uncertainty-Calibrated MOPD

arXiv:2608.26735v1 Announce Type: new Abstract: Specializing large language models to vertical domains improves domain-specific behavior but often degrades general capabilities such as reasoning, codi

Reason in the Words You Speak: Idiolectal Paraphrasing Off-Policy Traces for Reasoning Distillation in VideoLLMs

arXiv:2608.26684v1 Announce Type: new Abstract: Recent large language models achieve strong performance on complex reasoning tasks, where reinforcement learning with Group Relative Policy Optimization

Refine-POI: Reinforcement Fine-Tuned Large Language Models for Next Point-of-Interest Recommendation

arXiv:2506.21599v5 Announce Type: replace-cross Abstract: Advancing large language models (LLMs) for the next point-of-interest (POI) recommendation task faces two fundamental challenges: (i) although

Model Releases

Refusal Is Not Robustness: Auditing Confident Fabrication in Large Language Models on a Provably Uninformative Clinical Pain Speech Transcript

model-releasesarxiv-cs-ai

arXiv:2608.26167v1 Announce Type: new Abstract: Hallucination and abstention benchmarks rarely establish that a model could not have known the correct answer, making it difficult to distinguish approp

Research Design Tracking and Assessment for the Social Sciences

arXiv:2608.27049v1 Announce Type: new Abstract: Reliable assessment of causal research designs in the social sciences is critical for evidence-based policy-making, yet has so far relied entirely on ma

Residual Deep Reinforcement Learning-Based Computed Torque Control for a Cable-Driven Lower-Limb Rehabilitation Robot under Disturbances and Parametric Uncertainties

arXiv:2608.26739v1 Announce Type: new Abstract: Accurate trajectory tracking in cable-driven lower-limb rehabilitation robots is challenging because model uncertainty, external disturbances, joint con

safetyarxiv-cs-ro

Residual Reward Models: Leveraging Prior Knowledge for Efficient Preference-based Reinforcement Learning in Robotics

arXiv:2507.00611v2 Announce Type: replace-cross Abstract: Preference-based Reinforcement Learning (PbRL) provides a promising alternative to heuristic reward design in complex robotic environments. Ho

SAGE: Variate-Wise Semantic Augmentation for Vision-Language Time Series Forecasting

arXiv:2608.26829v1 Announce Type: cross Abstract: Time series forecasting models operate on raw numerical sequences, lacking the semantic knowledge that domain experts implicitly leverage, such as the

Selection Bias Correction in Retail Intelligence

arXiv:2608.26156v1 Announce Type: new Abstract: Retail intelligence often relies on monitoring popular, high-velocity products, potentially biasing economic indicators by ignoring the 'long tail' of n

Self-OPD: On-Policy Distillation for Flow Matching Models without Teacher

arXiv:2608.26872v1 Announce Type: new Abstract: On-policy distillation (OPD), which leverages a pre-trained, specialized teacher model to provide dense supervisory signals, has achieved significant su

Shared Actors Need Not Share Critics: Effects of Value Mismatch in Parallel Reinforcement Learning

arXiv:2608.26481v1 Announce Type: new Abstract: When a single policy is trained in parallel across multiple environments of the same task, such as procedurally generated levels, randomized dynamics, o

SHIFT: Semantic Harmonization via Index-side Feature Transformation for Multilingual Information Retrieval

arXiv:2606.18801v2 Announce Type: replace-cross Abstract: With the rapid expansion of massive multilingual corpora, Multilingual Information Retrieval (MLIR) has emerged as a critical technology for g

Sidecar: Training-Free Semantic Reuse for Character-Consistent Free-form Visual Storytelling

arXiv:2608.27280v1 Announce Type: new Abstract: Visual storytelling requires generating images that follow a narrative while preserving consistent character identities across frames. In free-form stor

SimCast-S2S: An Efficient Generative Model for Subseasonal Precipitation Forecasting via Transfer Learning from Climate Simulations

arXiv:2608.26594v1 Announce Type: new Abstract: Subseasonal-to-seasonal (S2S) precipitation forecasting has substantial financial and societal impact, yet remains challenging because of weak predictiv

Simultaneous Envy and Equitability Guarantees

arXiv:2608.26410v1 Announce Type: cross Abstract: Recent work in fair division has focused on either simultaneously satisfying closely related fairness notions or achieving a single notion across the

SkillChain: Closing the Loop on Skill Evolution for Image-Based E-Commerce AI Assistants

arXiv:2606.12984v2 Announce Type: replace Abstract: Image-based AI assistants are now deployed at production scale on e-commerce platforms, where a single uploaded image can trigger fundamentally diff

SPEAR: Distilling Domain-Adaptive Reasoning Skeletons via Sequential Symbolic Alignment in Reinforcement Learning

arXiv:2608.26550v1 Announce Type: new Abstract: Reinforcement learning-based knowledge distillation has the potential to transfer complex reasoning from teacher to student models, yet it currently fac