Search: “safety”

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arXiv:2608.30188v1 Announce Type: new Abstract: Large Language Models (LLMs) show great potential as clinical agents, yet existing benchmarks reduce clinical workflows to static predictions or unconst

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Graph Evidence Is Not Enough: Diagnosing Native Decoder Use in Graph-Augmented LLMs

DGX agent

arXiv:2608.30437v1 Announce Type: new Abstract: Graph-augmented large language models often assume that graph evidence produced by external computation and placed in the input can be used by the nativ

safetyarxiv-cs-cl

1 Sept 2026

GuardianAgent: Policy-Conditioned Risk-Adaptive Anonymization with Verified Adversarial Escalation

arXiv:2608.29251v1 Announce Type: new Abstract: Privacy protection for live web traffic requires more than detecting private spans. Agent-based privacy protection systems must determine whether an out

Hearing the Order: Investigating Position Bias in Large Audio-Language Models

arXiv:2510.00628v3 Announce Type: replace-cross Abstract: Large audio-language models (LALMs) are often used in tasks that involve reasoning over ordered options. An open question is whether their pre

Hidden Threat in Synthetic Data: Covert Targeted Bias Injection through Benign Text

arXiv:2608.30619v1 Announce Type: cross Abstract: Synthetic data is increasingly used to train large language models (LLMs), yet its security implications remain poorly understood. Prior work on subli

Hindsight Memory-PRM: Supervising Memory Management with Auditable Hindsight Credit

arXiv:2608.29605v1 Announce Type: new Abstract: Memory operations of long-horizon LLM agents are hard to supervise: an operation's value is unobservable when it is taken. But they are special -- they

HoopMind: A Real-Time Neural Game-Tree System for Opponent-Aware Possession Planning

arXiv:2608.29563v1 Announce Type: cross Abstract: School coaches prepare for opponents with game film and intuition. The analytics tools of professional teams stay out of reach. We ask how far public

I think there is a problem even worse than anthropomorphism. These days, everyone is talking about a blog post by Dwarkesh Patel that descri…

I think there is a problem even worse than anthropomorphism. These days, everyone is talking about a blog post by Dwarkesh Patel that describes the OpenAI–Hugging Face incident in dystopian, anthropom

safetygary-marcus--x

In an interview in this article for The @guardian about AI deception, I explain why misaligned behaviors emerge from reinforcement learning,…

In an interview in this article for The @guardian about AI deception, I explain why misaligned behaviors emerge from reinforcement learning, why they will continue to pose risks as models become more

safetyyoshua-bengio--x

Influence-Directed Distillation: Solving the Diversity Bottleneck in Sampled-Token On-Policy Distillation

arXiv:2608.29846v1 Announce Type: new Abstract: Sampled-token on-policy distillation (OPD) efficiently transfers capabilities from teacher to student using student-generated tokens, requiring teacher

InLiER: Learning-Free Heterogeneous LiDAR Place Recognition via Intermediate Mixed-Radix Structural Keypoint Tokenization

arXiv:2607.16862v2 Announce Type: replace Abstract: LiDAR place recognition supports loop closure, relocalization, and multi-agent map management. As robotic platforms increasingly combine LiDARs with

InspectorGPT: A Comparative Reasoning Enhanced VLM for Comprehensive Industrial Anomaly Detection

arXiv:2608.29783v1 Announce Type: new Abstract: Industrial anomaly detection is a critical component of modern manufacturing. Most traditional unsupervised methods rely on modelling normal feature dis

Integrating adaptive human behavior into epidemic models with large language models

arXiv:2608.29535v1 Announce Type: cross Abstract: Infectious disease transmission is shaped by patterns of human interaction, which adapt as epidemic conditions change. Capturing these context-depende

InternReviewer & InternAdvocate: Objective Reward and Evaluation for Agentic Reinforcement Learning in Peer Review and Rebuttal

arXiv:2608.28612v1 Announce Type: new Abstract: Generating professional scholarly content, such as peer reviews and rebuttals, requires an intricate synergy between domain reasoning and factual ground

JPO: Juris Policy Optimization for Structured Legal Reasoning in Criminal Judgment Prediction

arXiv:2608.29616v1 Announce Type: new Abstract: Criminal judgment prediction requires models to infer statutory articles, charges, and sentencing outcomes from case facts. Unlike standard classificati

Label Semantic Expansion via Label Guided Neural Topic Modeling

arXiv:2608.30216v1 Announce Type: cross Abstract: Topic models are widely used for content analysis, where users often analyze corpora around predefined labels rather than unordered latent topics. Exi

Labels have Human Values: Value Calibration of Subjective Tasks

arXiv:2601.06631v2 Announce Type: replace Abstract: Building NLP systems for subjective tasks requires one to ensure their alignment to contrasting human values. We propose the MultiCalibrated Subject

Latent-Space Intervention for Cross-Lingual Factual Consistency: Consistency Improvements without Accuracy Drops

arXiv:2608.28860v1 Announce Type: new Abstract: Large Language Models (LLMs) often answer the same factual question differently across languages. We study whether cross-lingual latent-space interventi

Learning Agile Perceptive Traversal of Sparse 3D Structures for Humanoids

arXiv:2608.29769v1 Announce Type: new Abstract: Traversing sparse 3D structures requires humanoid robots to perceive thin, overhanging geometry while executing agile, accurate whole-body motions. We s

safetyarxiv-cs-ro

Learning Dynamics of Logits Debiasing for Long-Tailed Semi-Supervised Learning

arXiv:2608.30699v1 Announce Type: cross Abstract: Long-tailed distributions are prevalent in real-world semi-supervised learning (SSL), where pseudo-labels tend to favor majority classes, leading to d

Learning from What You Retrieve: Online RL Fine-Tuning for Semantic Retrieval

arXiv:2608.30753v1 Announce Type: cross Abstract: In large-scale e-commerce retrieval, dual-encoder retrievers are op- timized for contrastive similarity, whereas downstream rerankers capture finer-gr

Liquid Gated Attention

arXiv:2608.30695v1 Announce Type: new Abstract: Real-world time series often exhibit irregular sampling and extended temporal horizons, requiring models to capture continuous-time dynamics across arbi

LLP: LLM-Based Product Pricing in E-commerce

arXiv:2510.09347v2 Announce Type: replace Abstract: Unlike Business-to-Consumer e-commerce platforms (e.g., Amazon), inexperienced individual sellers on Consumer-to-Consumer platforms (e.g., eBay) oft

Locally-Guided Actor-Critic: Training a Goal-conditioned Actor with a Subgoal-aware Critic

arXiv:2608.30406v1 Announce Type: new Abstract: Goal-conditioned reinforcement learning struggles with long horizons when rewards are sparse. While a planner can provide subgoals to guide a low-level

Low-Resource Preference Adaptation of LLMs via Activation-Based Label Propagation

arXiv:2608.30902v1 Announce Type: new Abstract: Adapting large language models to user-specific preferences is often constrained by the cost of human annotation, making preference optimisation impract

Lucida: Parse, Generate, and Place for Composable Real-to-Sim Scene Modeling

arXiv:2608.30821v1 Announce Type: cross Abstract: Composable scene modeling aims to recover a real indoor scene as complete, editable object assets arranged as observed, giving robot simulation and em

ManGo: Manga Active Narrative Grounding Optimization

arXiv:2608.29865v1 Announce Type: new Abstract: Manga visual question answering requires models to answer questions over panel-based visual narratives, where relevant evidence is distributed across or

Measurement Validity in LLM Cultural Alignment

arXiv:2608.29266v1 Announce Type: cross Abstract: Researchers increasingly treat LLM survey responses as a proxy for human cultural values. This includes projecting model outputs onto instruments like

MERIT: Mitigating Exposure Bias in Generative XMC for User-Interest Propensity Modeling

arXiv:2608.28931v1 Announce Type: cross Abstract: Matching users to interest categories at scale is central to personalized shopping, but the task is challenging in large e-commerce platforms, where l

Mind the Gap: Theory-of-Mind-Grounded Friction for Epistemic Alignment

arXiv:2608.30719v1 Announce Type: new Abstract: Productive dialogue alignment requires distinguishing surface coordination (acknowledgments and smooth task progression) from epistemic alignment (conve

Motus2: A Self-Evolving General World Model for Dexterous Manipulation

arXiv:2608.30237v1 Announce Type: cross Abstract: General embodied agents should perceive, predict, act, evaluate, and improve within a unified system. World models have shown great promise in buildin

Multi-exposure HDR Imaging: A Review of Pixel-level and Feature-level Reconstruction Methods

arXiv:2608.28674v1 Announce Type: new Abstract: Multi-exposure is an efficient way to capture real-world high-dynamic-range (HDR) scenes. However, HDR imaging suffers from severe ghosting artifacts in

Multiclass Linear Perceptrons with Multiplicative Margins

arXiv:2608.30028v1 Announce Type: new Abstract: This paper introduces a family of multiclass linear Perceptron classifiers with a multiplicative margin mechanism (MMPerc), as an alternative to standar

Multimodal Shared Latent Representation of Narration, Microscope and iOCT Images for Phase Recognition in Vitreoretinal Surgery

arXiv:2608.31065v1 Announce Type: new Abstract: Surgical phase recognition is key to context-aware computer-assisted feedback in vitreoretinal procedures, yet the scarcity of synchronized multimodal i

NBS: No Bias Stereo

arXiv:2608.28933v1 Announce Type: new Abstract: Stereo reconstruction is one of the last remaining Computer Vision tasks where all state-of-the-art methods employ a heavy architectural inductive bias.

@NJHagens Great summary of the fiasco:

@NJHagens Great summary of the fiasco: A detailed deconstruction of @dwarkesh_sp’s wildly popular but dangerously misleading account of the OpenAI Hugging Face incident: https://garymarcus.substack.co

safetygary-marcus--x

NoisEasier: Test-Time Noise Optimization for Text-to-Video Generation

arXiv:2608.30194v1 Announce Type: new Abstract: Diffusion models have recently advanced text-to-video (T2V) generation, yet they still struggle with fine-grained compositional alignment, such as attri

Nonparametric Contextual Pricing and Inventory Learning under Censored Demand

arXiv:2608.30944v1 Announce Type: new Abstract: In online retailing, when a product sells out, a retailer often sees only the units sold, not how many customers would have bought it had inventory been

Not Your Typical Sycophant: The Elusive Nature of Sycophancy in Large Language Models

arXiv:2601.15436v3 Announce Type: replace Abstract: We propose a novel perspective for probing LLM sycophancy in a direct and neutral way, mitigating various forms of uncontrolled bias, noise, or mani

Off-Policy Evaluation for Semantic ID Recommenders: Does the Model's Own Code Hierarchy Help?

arXiv:2608.28905v1 Announce Type: new Abstract: Generative recommenders increasingly emit semantic IDs (SIDs): each item is a short sequence of hierarchical discrete codes from a residual quantizer, d

Online Estimation of Dynamic Origin-Destination Matrices Using Reinforcement Learning with Link-Flow Propagation Guidance

arXiv:2608.30317v1 Announce Type: cross Abstract: Online dynamic origin-destination (OD) matrix estimation (DODE) calibrates time-dependent OD demand to reproduce observed link-flow trajectories. In o

OPAL: Orthonormal Prototype Alignment Learning for Interpretable Image Classification

arXiv:2608.30003v1 Announce Type: new Abstract: Prototypical part-based models provide explainable predictions by comparing input regions to learned prototypes. However, current approaches are burdene

Optimally Selecting Representative Agents from a Metric Space

arXiv:2608.29097v1 Announce Type: cross Abstract: This paper studies the problem of proportionally fair clustering, where the goal is to select k ``centers'' from a metric space that fairly represent

OPUS: A Simple yet Effective Unified Framework for Open-Vocabulary Detection

arXiv:2608.30247v1 Announce Type: new Abstract: Recent unified open-vocabulary detection (OVD) supports heterogeneous prompts, including text queries, visual exemplars, and their combinations, but oft

PA3: Policy-Aware Agent Alignment through Chain-of-Thought

arXiv:2603.14602v3 Announce Type: replace-cross Abstract: Conversational assistants powered by large language models (LLMs) excel at tool-use tasks but struggle with adhering to complex, business-spec

PAC: Progress-Augmented Advantage Curriculum for Multi-Task Reinforcement Learning of LLMs

arXiv:2608.30528v1 Announce Type: new Abstract: Reinforcement learning (RL) is used to improve the reasoning abilities of LLMs, while training data span heterogeneous tasks. However, most RL post-trai

PathBridger: Subgoal Bridges for Offline Goal-Conditioned Reinforcement Learning

arXiv:2608.29061v1 Announce Type: new Abstract: Offline goal-conditioned reinforcement learning (GCRL) aims to learn policies for reaching diverse goals entirely from fixed trajectory data. Long-horiz

PAVE: Predictive Alignment and Value-Guided Evolution for World-Action Policies

arXiv:2608.30378v1 Announce Type: cross Abstract: Direct vision-language-action policies generate continuous robot actions efficiently, but standard behavior cloning leaves two complementary gaps: the