safety

Hybrid Latents -- Geometry-Appearance-Aware Surfel Splatting

arXiv:2604.14928v1 Announce Type: new Abstract: We introduce a hybrid Gaussian-hash-grid radiance representation for reconstructing 2D Gaussian scene models from multi-view images. Similar to NeST spl

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Safety

I went on @BBCNewsnight this week to discuss the recent developments in AI's capabilities, as well as the potential harms and concentration …

DGX agent

I went on @BBCNewsnight this week to discuss the recent developments in AI's capabilities, as well as the potential harms and concentration of power they could entail. We need coordinated internationa

safetyyoshua-bengio--x

17 Apr 2026

IG-Search: Step-Level Information Gain Rewards for Search-Augmented Reasoning

arXiv:2604.15148v1 Announce Type: cross Abstract: Reinforcement learning has emerged as an effective paradigm for training large language models to perform search-augmented reasoning. However, existin

Implicit Neural Representations: A Signal Processing Perspective

arXiv:2604.15047v1 Announce Type: new Abstract: Implicit neural representations (INRs) mark a fundamental shift in signal modeling, moving from discrete sampled data to continuous functional represent

Improving Machine Learning Performance with Synthetic Augmentation

arXiv:2604.14498v1 Announce Type: cross Abstract: Synthetic augmentation is increasingly used to mitigate data scarcity in financial machine learning, yet its statistical role remains poorly understoo

in 1996 mitzenmacher showed that sampling two backends and picking the better one drops max load exponentially vs. random selection one extr…

in 1996 mitzenmacher showed that sampling two backends and picking the better one drops max load exponentially vs. random selection one extra comparison. that's the whole trick we built pinecone assis

safetypinecone--x

Inclusive Kitchen Design for Older Adults: Generative AI Visualizations to Support Mild Cognitive Impairment

arXiv:2604.13203v1 Announce Type: cross Abstract: Mild Cognitive Impairment (MCI) affects 15-20% of adults aged 65 and older, often making kitchen navigation and independent living difficult, particul

Integrating Object Detection, LiDAR-Enhanced Depth Estimation, and Segmentation Models for Railway Environments

arXiv:2604.14781v1 Announce Type: new Abstract: Obstacle detection in railway environments is crucial for ensuring safety. However, very few studies address the problem using a complete, modular, and

IROSA: Interactive Robot Skill Adaptation using Natural Language

arXiv:2603.03897v3 Announce Type: replace-cross Abstract: Foundation models have demonstrated impressive capabilities across diverse domains, while imitation learning provides principled methods for r

Language Model as Planner and Formalizer under Constraints

arXiv:2510.05486v2 Announce Type: replace Abstract: LLMs have been widely used in planning, either as planners to generate action sequences end-to-end, or as formalizers to represent the planning doma

Language of Thought Shapes Output Diversity in Large Language Models

arXiv:2601.11227v2 Announce Type: replace Abstract: Output diversity is crucial for Large Language Models as it underpins pluralism and creativity. In this work, we reveal that controlling the languag

Language on Demand, Knowledge at Core: Composing LLMs with Encoder-Decoder Translation Models for Extensible Multilinguality

arXiv:2603.17512v4 Announce Type: replace Abstract: Large language models (LLMs) exhibit strong general intelligence, yet their multilingual performance remains highly imbalanced. Although LLMs encode

Layered Mutability: Continuity and Governance in Persistent Self-Modifying Agents

arXiv:2604.14717v1 Announce Type: cross Abstract: Persistent language-model agents increasingly combine tool use, tiered memory, reflective prompting, and runtime adaptation. In such systems, behavior

LeapAlign: Post-Training Flow Matching Models at Any Generation Step by Building Two-Step Trajectories

arXiv:2604.15311v1 Announce Type: new Abstract: This paper focuses on the alignment of flow matching models with human preferences. A promising way is fine-tuning by directly backpropagating reward gr

Learning Ad Hoc Network Dynamics via Graph-Structured World Models

arXiv:2604.14811v1 Announce Type: new Abstract: Ad hoc wireless networks exhibit complex, innate and coupled dynamics: node mobility, energy depletion and topology change that are difficult to model a

Learning Adaptive Reasoning Paths for Efficient Visual Reasoning

arXiv:2604.14568v1 Announce Type: cross Abstract: Visual reasoning models (VRMs) have recently shown strong cross-modal reasoning capabilities by integrating visual perception with language reasoning.

Learning to Think Like a Cartoon Captionist: Incongruity-Resolution Supervision for Multimodal Humor Understanding

arXiv:2604.15210v1 Announce Type: cross Abstract: Humor is one of the few cognitive tasks where getting the reasoning right matters as much as getting the answer right. While recent work evaluates hum

MARS^2: Scaling Multi-Agent Tree Search via Reinforcement Learning for Code Generation

arXiv:2604.14564v1 Announce Type: cross Abstract: Reinforcement learning (RL) paradigms have demonstrated strong performance on reasoning-intensive tasks such as code generation. However, limited traj

Mean Flow Policy Optimization

arXiv:2604.14698v1 Announce Type: new Abstract: Diffusion models have recently emerged as expressive policy representations for online reinforcement learning (RL). However, their iterative generative

Meituan Merchant Business Diagnosis via Policy-Guided Dual-Process User Simulation

arXiv:2604.15190v1 Announce Type: cross Abstract: Simulating group-level user behavior enables scalable counterfactual evaluation of merchant strategies without costly online experiments. However, bui

Metric-Aware Principal Component Analysis (MAPCA):A Unified Framework for Scale-Invariant Representation Learning

arXiv:2604.14249v1 Announce Type: new Abstract: We introduce Metric-Aware Principal Component Analysis (MAPCA), a unified framework for scale-invariant representation learning based on the generalised

Model-Free Assessment of Simulator Fidelity via Quantile Curves

arXiv:2512.05024v3 Announce Type: replace-cross Abstract: As generative AI models are increasingly used to simulate real-world systems, quantifying the ``sim-to-real'' gap is critical. For each input

Modeling LLM Unlearning as an Asymmetric Two-Task Learning Problem

arXiv:2604.14808v1 Announce Type: new Abstract: Machine unlearning for large language models (LLMs) aims to remove targeted knowledge while preserving general capability. In this paper, we recast LLM

Momentum-constrained Hybrid Heuristic Trajectory Optimization Framework with Residual-enhanced DRL for Visually Impaired Scenarios

arXiv:2604.14986v1 Announce Type: new Abstract: Safe and efficient assistive planning for visually impaired scenarios remains challenging, since existing methods struggle with multi-objective optimiza

safetyarxiv-cs-ro

Multi-Modal Manipulation via Multi-Modal Policy Consensus

arXiv:2509.23468v3 Announce Type: replace-cross Abstract: Effectively integrating diverse sensory modalities is crucial for robotic manipulation. However, the typical approach of feature concatenation

Multi-Persona Thinking for Bias Mitigation in Large Language Models

arXiv:2601.15488v2 Announce Type: replace Abstract: Large Language Models (LLMs) exhibit social biases, which can lead to harmful stereotypes and unfair outcomes. We propose extbf{Multi-Persona Thinki

Multi-User mmWave Beam and Rate Adaptation via Combinatorial Satisficing Bandits

arXiv:2604.14908v1 Announce Type: new Abstract: We study downlink beam and rate adaptation in a multi-user mmWave MISO system where multiple base stations (BSs), each using analog beamforming from fin

Neuro-Symbolic AI for Cybersecurity: State of the Art, Challenges, and Opportunities

arXiv:2509.06921v2 Announce Type: replace-cross Abstract: Cybersecurity demands both rapid pattern recognition and deliberative reasoning, yet purely neural or purely symbolic approaches each address

NG-GS: NeRF-Guided 3D Gaussian Splatting Segmentation

arXiv:2604.14706v1 Announce Type: new Abstract: Recent advances in 3D Gaussian Splatting (3DGS) have enabled highly efficient and photorealistic novel view synthesis. However, segmenting objects accur

NLP needs Diversity outside of 'Diversity'

arXiv:2604.14595v1 Announce Type: new Abstract: This position paper argues that recent progress with diversity in NLP is disproportionately concentrated on a small number of areas surrounding fairness

OmniCompliance-100K: A Multi-Domain, Rule-Grounded, Real-World Safety Compliance Dataset

arXiv:2603.13933v2 Announce Type: replace Abstract: Ensuring the safety and compliance of large language models (LLMs) is of paramount importance. However, existing LLM safety datasets often rely on a

Optimistic Policy Learning under Pessimistic Adversaries with Regret and Violation Guarantees

arXiv:2604.14243v1 Announce Type: new Abstract: Real-world decision-making systems operate in environments where state transitions depend not only on the agent's actions, but also on extbf{exogenous f

ORBIT: On-policy Exploration-Exploitation for Controllable Multi-Budget Reasoning

arXiv:2601.08310v2 Announce Type: replace Abstract: Recent Large Reasoning Models (LRMs) achieve strong performance by leveraging long-form Chain-of-Thought (CoT) reasoning, but uniformly applying ove

Practical estimation of the optimal classification error with soft labels and calibration

arXiv:2505.20761v3 Announce Type: replace Abstract: While the performance of machine learning systems has experienced significant improvement in recent years, relatively little attention has been paid

Preconditioned Test-Time Adaptation for Out-of-Distribution Debiasing in Narrative Generation

arXiv:2603.13683v2 Announce Type: replace Abstract: Although debiased large language models (LLMs) excel at handling known or low-bias prompts, they often fail on unfamiliar and high-bias prompts. We

ProRe: A Proactive Reward System for GUI Agents via Reasoner-Actor Collaboration

arXiv:2509.21823v2 Announce Type: replace Abstract: Reward is critical to the evaluation and training of large language models (LLMs). However, existing rule-based or model-based reward methods strugg

PROXIMA: A Reliability Scoring Framework for Proxy Metrics in Online Controlled Experiments

arXiv:2604.14352v1 Announce Type: cross Abstract: Online A/B testing at scale relies on proxy metrics -- short-term, easily-measured signals used in place of slow-moving long-term outcomes. When the p

Pushing the Boundaries of Multiple Choice Evaluation to One Hundred Options

arXiv:2604.14634v1 Announce Type: new Abstract: Multiple choice evaluation is widely used for benchmarking large language models, yet near ceiling accuracy in low option settings can be sustained by s

QU-NLP at ArchEHR-QA 2026: Two-Stage QLoRA Fine-Tuning of Qwen3-4B for Patient-Oriented Clinical Question Answering and Evidence Sentence Alignment

arXiv:2604.14175v1 Announce Type: new Abstract: We present a unified system addressing both Subtask 3 (answer generation) and Subtask 4 (evidence sentence alignment) of the ArchEHR-QA Shared Task. For

R3D: Revisiting 3D Policy Learning

arXiv:2604.15281v1 Announce Type: new Abstract: 3D policy learning promises superior generalization and cross-embodiment transfer, but progress has been hindered by training instabilities and severe o

RAD-2: Scaling Reinforcement Learning in a Generator-Discriminator Framework

arXiv:2604.15308v1 Announce Type: new Abstract: High-level autonomous driving requires motion planners capable of modeling multimodal future uncertainties while remaining robust in closed-loop interac

RaTA-Tool: Retrieval-based Tool Selection with Multimodal Large Language Models

arXiv:2604.14951v1 Announce Type: cross Abstract: Tool learning with foundation models aims to endow AI systems with the ability to invoke external resources -- such as APIs, computational utilities,

Reasoning Dynamics and the Limits of Monitoring Modality Reliance in Vision-Language Models

arXiv:2604.14888v1 Announce Type: new Abstract: Recent advances in vision language models (VLMs) offer reasoning capabilities, yet how these unfold and integrate visual and textual information remains

RECOVER: Designing a Large Language Model-based Remote Patient Monitoring System for Postoperative Gastrointestinal Cancer Care

arXiv:2502.05740v2 Announce Type: replace-cross Abstract: Cancer surgery is a key treatment for gastrointestinal (GI) cancers, a group of cancers that account for more than 35% of cancer-related death

Reinforcement Learning via Value Gradient Flow

arXiv:2604.14265v1 Announce Type: new Abstract: We study behavior-regularized reinforcement learning (RL), where regularization toward a reference distribution (the dataset in offline RL or the base m

Reward-Aware Trajectory Shaping for Few-step Visual Generation

arXiv:2604.14910v1 Announce Type: new Abstract: Achieving high-fidelity generation in extremely few sampling steps has long been a central goal of generative modeling. Existing approaches largely rely

RL-STPA: Adapting System-Theoretic Hazard Analysis for Safety-Critical Reinforcement Learning

arXiv:2604.15201v1 Announce Type: new Abstract: As reinforcement learning (RL) deployments expand into safety-critical domains, existing evaluation methods fail to systematically identify hazards aris

RoSLAC: Robust Simultaneous Localization and Calibration of Multiple Magnetometers

arXiv:2604.14353v1 Announce Type: new Abstract: Localization of autonomous mobile robots (AMRs) in enclosed or semi-enclosed environments such as offices, hotels, hospitals, indoor parking facilities,

safetyarxiv-cs-ro