Search: “safety”

GRRM: Group Relative Reward Modeling for Machine Translation

arXiv:2602.14028v2 Announce Type: replace Abstract: While Group Relative Policy Optimization (GRPO) offers a powerful framework for LLM post-training, its effectiveness in open-ended domains like Mach

HEAL: Hindsight Entropy-Assisted Learning for Reasoning Distillation

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DGX agent

arXiv:2603.10359v2 Announce Type: replace Abstract: Distilling reasoning capabilities from Large Reasoning Models (LRMs) into smaller models is typically constrained by the limitations of rejection sa

safetyarxiv-cs-ai

2 Sept 2026

Heard but Not Heeded: Paralinguistic Information Encoding and Loss in Audio-Language Models

arXiv:2609.00727v1 Announce Type: cross Abstract: Audio language models are designed to understand speech, yet it remains unclear whether they capture how something is said beyond what is said. We pre

HiMPO: Hindsight-Informed Memory Policy Optimization for Less-Entangled Credit in Long-Horizon Agents

arXiv:2606.16285v2 Announce Type: replace Abstract: Long-horizon agents rely on memory mechanisms to compress interaction history, but optimizing memory writing faces a distinct credit assignment chal

How Does Alignment Tuning Shape Representations of Sycophancy and Related Cue-Induced Biases in LLMs?

arXiv:2607.18114v2 Announce Type: replace-cross Abstract: Modern LLMs are alarmingly susceptible to surprisingly simple immaterial changes of input prompts: a casual hint, an incorrectly labeled few-s

Human-AI Co-Interpretation for Responsible AI: A Hermeneutic Perspective

arXiv:2609.00334v1 Announce Type: new Abstract: Across law, education, policy analysis, and public moral argumentation, LLM outputs are being used often for work that requires interpretations to be ju

Human-Anchored Factuality Evaluation with Strategic Annotation

arXiv:2609.00494v1 Announce Type: new Abstract: LLM-based factuality judges provide scalable evaluation signals, but their metrics are often systematically biased relative to human judgments. We study

HyperWorld: Hypergraph-Structured State Serialization Improves Learned Textual World Models

arXiv:2609.00002v1 Announce Type: new Abstract: World models enable language-model agents to predict environment dynamics and plan before acting. In text environments, the model must learn symbolic ac

If this is true, OpenAI seems to be violating one of the few redlines that exist in the AI industry. Absolutely do not train your models lik…

If this is true, OpenAI seems to be violating one of the few redlines that exist in the AI industry. Absolutely do not train your models like this - what is going on?? Really huge and extremely concer

In case you're wondering while this steaming POS is being floated now, it's because SoftBank needs to refinance the $40B bridge loan it used…

In case you're wondering while this steaming POS is being floated now, it's because SoftBank needs to refinance the 40B bridge loan it used to invest 30B into OpenAI before it matures in March 2027...

Investigating Assistant Bias in LLM User Simulators Using a Role Vector

arXiv:2609.00608v1 Announce Type: new Abstract: LLM-based user simulators are increasingly used to evaluate autonomous agents at scale, in place of costly human evaluations. Despite this promise, thes

Iterative GRPO: Batch-Online Policy Iteration for Multi-Turn RL via Single-Turn RLHF

arXiv:2511.21638v2 Announce Type: replace Abstract: Practical LLM agents often operate over multi-turn conversations where success is determined only after the full interaction ends. Most multi-turn R

safetyarxiv-cs-lg

JanusMesh: Fast and Zero-Shot 3D Visual Illusion Generation via Cross-Space Denoising

arXiv:2606.20563v2 Announce Type: replace Abstract: Creating 3D visual illusions, a single 3D mesh that reveals entirely different semantics from various viewing angles, is a fascinating but tough cha

Keep Everyone Happy: Online Fair Division of Numerous Items with Few Copies

arXiv:2408.12845v3 Announce Type: replace-cross Abstract: This paper considers a novel variant of the online fair division problem involving multiple agents in which a learner sequentially observes an

Knowing When to Stop: Adaptive Action Chunking via Internal Cross-Attention Dynamics in VLAs

arXiv:2609.00908v1 Announce Type: new Abstract: Action chunking is a standard execution strategy in modern Vision-Language-Action (VLA) frameworks, but fixed execution horizons impose a trade-off betw

safetyarxiv-cs-ro

Legible chain of thought was extremely useful for our independent investigation into the OpenAI/Hugging Face incident. Developments like thi…

Legible chain of thought was extremely useful for our independent investigation into the OpenAI/Hugging Face incident. Developments like this may make third-party auditing much more difficult and make

LLM-as-a-Demographic: Whom Sociodemographic Prompting Helps, and Whom It Hurts

arXiv:2609.00222v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used as judges for subjective tasks, where annotators disagree and the relevant question is not only how a

Location-Aware Language Models via Secondary Embeddings

arXiv:2609.00454v1 Announce Type: new Abstract: Pretrained transformer-based language models achieve strong performance across a wide range of NLP tasks but remain limited in encoding geo-locational s

Measuring the Behavioral Fidelity of Long-Horizon Human Activity Simulations

arXiv:2609.01257v1 Announce Type: new Abstract: As LLM-based human simulators are increasingly used for policy, evaluation, and training, they must faithfully reproduce real behavioral patterns. While

Multi-Step Knowledge Interaction Analysis via Rank-2 Subspace Disentanglement

arXiv:2511.01706v3 Announce Type: replace-cross Abstract: Natural Language Explanations (NLEs) describe how Large Language Models (LLMs) make decisions by drawing on external Context Knowledge (CK) an

Nobody can predict the future with perfect accuracy, but I am increasingly confident that by the end of decade, generative AI (at least we k…

Nobody can predict the future with perfect accuracy, but I am increasingly confident that by the end of decade, generative AI (at least we know it) will be viewed as on balance a tragic, costly mistak

Non-Prehensile Throwing: A Reinforcement Learning Perspective

arXiv:2609.00771v1 Announce Type: new Abstract: Robotic throwing enables fast object transport and extends a robot's reachable workspace beyond traditional pick-and-place. While prehensile (grasp-base

safetyarxiv-cs-ro

On the Design Fundamentals of Pixel Text Representation Learning

arXiv:2609.01147v1 Announce Type: cross Abstract: Text-rich visual inputs require models that can read, retrieve, and compress language directly in pixel space, yet existing pixel-text encoders strugg

On the Human and Computer Alignment of Attribute-Based Music Matches

arXiv:2609.00987v1 Announce Type: cross Abstract: Recent advances in generative AI are raising ethical concerns regarding the originality of generated content and the potential replication of training

One Policy, Any Budget: Internalizing Budget-Aware Search via Reinforcement Learning

arXiv:2609.00813v1 Announce Type: new Abstract: While reinforcement learning has enabled LLM-based search agents to invoke external tools, existing methods train under fixed budgets and cannot adapt w

Online camera-pose-free stereo endoscopic tissue deformation recovery with tissue-invariant vision-biomechanics consistency

arXiv:2506.19388v2 Announce Type: replace Abstract: Tissue deformation recovery based on stereo endoscopic images is crucial for tool-tissue interaction analysis and benefits surgical navigation and a

Ov3R: Open-Vocabulary Semantic 3D Reconstruction from RGB Videos

arXiv:2507.22052v3 Announce Type: replace Abstract: We present Ov3R, a novel framework for open-vocabulary semantic 3D reconstruction from RGB video streams, designed to advance Spatial AI. The system

Post-hoc Alignment of LLM-judges to Human Judgment Distribution

arXiv:2609.01073v1 Announce Type: new Abstract: The LLM-as-a-judge (LLMaJ) framework offers a cost-effective and reproducible solution for automatic evaluation. However, current evaluation practices t

Prompt-Robust Language Models: Which Training Strategies Work?

arXiv:2609.01217v1 Announce Type: new Abstract: Despite their strong performance, large language models remain highly sensitive to prompt formulation. Prior work addresses this through refined data co

Provably Efficient Federated Reinforcement Learning with Linear Function Approximation and Logarithmic Communication Cost

arXiv:2609.00193v1 Announce Type: cross Abstract: We study federated online reinforcement learning with linear function approximation. While recent multi-agent reinforcement learning algorithms achiev

ProxPI: Proximal Prior Injection for Sampling-Based MPC under Learned-Prior Mismatch

arXiv:2609.00941v1 Announce Type: new Abstract: Combining learned policies with model predictive control can leverage learned task priors while retaining online adaptation to new objectives and constr

safetyarxiv-cs-ro

Puppeteer: Object-Grounded Posture-Aware Co-Speech Gesture Generation

arXiv:2609.00369v1 Announce Type: new Abstract: Generating co-speech gestures that are temporally coherent, semantically aligned with speech, and grounded with surrounding objects remains challenging.

Ready to Speak: Aligning LLMs for TTS-Friendly Text Generation

arXiv:2609.01246v1 Announce Type: new Abstract: Current Large Language Models (LLMs) are primarily optimized for written text, often producing outputs that are grammatically correct and helpful yet po

RED ALERT, and I have never said that before: Hard agree with @sjgadler and @_NathanCalvin - what OpenAI is reportedly playing with is bad, …

RED ALERT, and I have never said that before: Hard agree with @sjgadler and @_NathanCalvin - what OpenAI is reportedly playing with is bad, redline crossing bad. Chain of thought monitorability is lim

ReFlowSET: Representation-Aligned Latent Flow Matching for SAR-to-EO Image Translation

arXiv:2609.00968v1 Announce Type: new Abstract: SAR-to-EO image translation aims to generate electro-optical (EO) imagery from synthetic aperture radar (SAR) observations. Existing latent diffusion ap

Reliability Challenges in Diffusion Vision-Language Models

arXiv:2609.01318v1 Announce Type: cross Abstract: Diffusion-based Large Vision-Language Models (dLVLMs) have recently emerged as a compelling alternative to autoregressive (AR) LVLMs, offering advanta

ReNFT: Repairing Mode Collapse in Reward Post-Training via Internal Probability-Mass Recalibration

arXiv:2609.00061v1 Announce Type: cross Abstract: Reward post-training of diffusion generators inevitably concentrates probability mass on a few reward-favored modes, a mode collapse that erases withi

Right Frame, Wrong Rule: Cultural Cues Expose the Financial Knowledge Gap They Were Meant to Close

arXiv:2609.00999v1 Announce Type: cross Abstract: When a question has valid answers under different normative frameworks, a language model must decide which framework to use and whether it can answer

Scaled Idempotence in Transformer Attention: Paired OV Geometry and Shared-Value Algebras

arXiv:2609.01129v1 Announce Type: new Abstract: We identify a recurrent algebraic regularity in Transformer attention: a sparse subset of effective OV operators T=OV^op nearly closes under composition

safetyarxiv-cs-lg

Scaling Near-Optimal SFT-RL Annotation Budget Allocation from Small to Large LLMs

arXiv:2609.01573v1 Announce Type: cross Abstract: How to divide a fixed annotation budget between supervised fine-tuning (SFT) and reinforcement learning (RL) during LLM post-training remains an open

Selective Agent Guidance via Entropy: Learning Autonomous Policies from Imperfect VLM Teachers

arXiv:2609.01567v1 Announce Type: new Abstract: Vision-Language Models (VLMs) provide useful priors for interactive decision-making, but using them directly as policies is expensive and brittle: they

SFAD: Speculative Factuality-Aware Decoding

arXiv:2609.00796v1 Announce Type: new Abstract: As one of the most critical challenges in large language models, contextual faithfulness directly determines their reliability in knowledge-intensive ap

Skill Following: Evaluating Actual Skill Use in Retrieval-Enabled LLM Agents

arXiv:2609.00549v1 Announce Type: new Abstract: Large Language Model (LLM) agents increasingly rely on external skills, yet standard evaluations obscure whether retrieving these skills actually helps.

Slow to See, Slow to Suppress: Understanding the Effects of Modality in Context-Memory Conflicts

arXiv:2609.00293v1 Announce Type: new Abstract: We investigate how vision-language models (VLMs) handle context-memory conflicts; that is, situations in which the model is given information in context

SMELT: Scaling Laws for Compute-Matched MoE Looped Transformers

arXiv:2609.01343v1 Announce Type: new Abstract: Looped Transformers increase effective depth by iterating a shared block of layers, but most evaluations compare at fixed model size, conflating archite

safetyarxiv-cs-lg

Software developers are the AI industry’s best customers. Is their experience also the most misleading experience possible for its economy-w…

Software developers are the AI industry’s best customers. Is their experience also the most misleading experience possible for its economy-wide scope? Roughly 80% of developers already use AI tools. C

Space Generative AI with Solar Energy Harvesting

arXiv:2609.01062v1 Announce Type: new Abstract: Satellites are emerging as promising platforms to extend generative artificial intelligence (AI) services to remote areas lacking terrestrial infrastruc

SpatialGuard: Harness-Guided Verifiable Spatial Reasoning for Text-to-Image Generation

arXiv:2609.01582v1 Announce Type: new Abstract: Complex 3D spatial text to image generation requires models to convert natural language into stable visual geometry, not merely semantic appearance. Exi