Search: “safety”

DAVET: Denoising-Aware Visual Evidence Trajectory Allocation for Diffusion Vision-Language Models

arXiv:2608.01821v1 Announce Type: new Abstract: Diffusion vision-language models (dVLMs) iteratively denoise masked responses while conditioning each denoising step on visual evidence, making visual c

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Deep Research Pretraining via Predictive Navigation

DGX agent

arXiv:2608.00432v1 Announce Type: new Abstract: Deep research agents are often trained on expensive, environment-grounded tool-use trajectories that require repeated retrieval, document inspection, an

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4 Aug 2026

DeepDefense: Robust Learning via Layer-Wise Gradient-Feature Alignment

arXiv:2511.13749v2 Announce Type: replace Abstract: Deep neural networks are known to be vulnerable to adversarial perturbations, which are small, carefully crafted inputs that lead to incorrect predi

Demystifying When and Why VLAs Fail in Contact-Rich Tasks and How to Fix Them

arXiv:2608.01402v1 Announce Type: new Abstract: We address the problem of understanding when and why Vision-Language-Action models struggle with contact-rich manipulation tasks that require precise ph

Developing Combined Manipulation and Locomotion Skills with Interaction Representation and Skill Composition

arXiv:2608.00208v1 Announce Type: new Abstract: This paper addresses how to enable a humanoid robot to learn motion policies based on developmental principles and combine policies to create more sophi

Diffusion Policy with Behavioral Advantage Correction for Offline Reinforcement Learning

arXiv:2608.02332v1 Announce Type: new Abstract: In offline reinforcement learning (RL), the distribution shift between behavioral data and the learned policy can lead to erroneous Q-value estimation,

Disentangled Contrastive Learning for Zero-Shot Multilingual Dense Retrieval

arXiv:2608.02189v1 Announce Type: cross Abstract: Multilingual dense retrieval aims to handle queries and documents across different languages based on a unified retriever model. The challenge lies in

Distill What the Student Can See: Fisher-Projected On-Policy Distillation for Vision-Language Models

arXiv:2608.01263v1 Announce Type: new Abstract: On-policy distillation (OPD) samples trajectories from the current student policy and minimizes token-level divergence between student and teacher next-

Distill Where You Fail: Recovering Learning Signals of Negative RL-Groups from Adaptive Teacher Guidance

arXiv:2608.00782v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) has become a standard paradigm for post-training large language models (LLMs). While Group Relativ

DocPO: Advancing Document Policy Optimization via Tailored Step-Aware Rewards

arXiv:2608.00536v1 Announce Type: new Abstract: Reinforcement learning (RL) for document parsing often relies on reference-based rewards rooted in edit distance (e.g., tree edit distance), yet it rema

Domain-Generalized Adaptive Semantic Communication for Collaborative Perception

arXiv:2608.00056v1 Announce Type: cross Abstract: We propose RSTA, a domain-generalized semantic communication framework enabling source-free V2X collaborative perception under both observation-domain

DPL: Depth-only Perceptive Humanoid Locomotion via Realistic Depth Synthesis and Cross-Attention Terrain Reconstruction

arXiv:2510.07152v3 Announce Type: replace Abstract: Recent advancements in legged robot perceptive locomotion have shown promising progress. However, terrain-aware humanoid locomotion remains largely

DreamTrajectory: Trajectory-Guided Action Generation with World Model Alignment for Mobile Manipulation

arXiv:2608.01381v1 Announce Type: new Abstract: Mobile manipulation requires a robot to coordinate base and arm motion under continuously changing viewpoints and contact conditions, within an action s

Driver2Map: Imitating Human Driving for Online High-Definition Map Construction

arXiv:2608.01338v1 Announce Type: new Abstract: High-definition (HD) maps are essential for autonomous driving systems. In constructing such maps, onboard multi-view camera images, standard-definition

Element-Aware Group Learning for E-Commerce Image Generation

arXiv:2608.00584v1 Announce Type: new Abstract: Recent advances in image generation and editing have made prompt quality a key bottleneck for e-commerce creatives. Vision-language models (VLMs) can ge

Ensemble of Unsupervised Deep Learning for Clustering Imbalanced Tabular Data

arXiv:2608.00346v1 Announce Type: new Abstract: Data imbalance poses a major challenge in supervised classification, where the majority-class bias contributes to false negatives and overestimates clas

Entity-Aware Sequence Transduction for Player-Centric Ball Action Spotting

arXiv:2608.01696v1 Announce Type: new Abstract: Player-centric ball action spotting requires temporally precise event detection together with actor attribution in crowded, partially observed multi-age

Evolutionary Curriculum Learning Improves Biological Sequence Modeling

arXiv:2608.00697v1 Announce Type: cross Abstract: Variational autoencoders (VAEs) trained on multiple sequence alignments (MSAs) have emerged as powerful generative models for biological sequences, wi

Experience-Calibrated Contrastive Decoding for Mitigating Hallucinations in LM-Based Text-to-Speech

arXiv:2608.00722v1 Announce Type: cross Abstract: Language model-based text-to-speech (LM-based TTS) remains vulnerable to speech hallucinations that deviate from the target text. Existing mitigation

Exploiting Intrinsic Duality for Multi-Hop Question Generation

arXiv:2608.00712v1 Announce Type: new Abstract: Multi hop question generation (MQG) aims to generate questions from multiple given documents and target answers, whereas question answering (QA) focuses

Fairness Auditing: Lower Bounds on Company Manipulation

arXiv:2608.00568v1 Announce Type: new Abstract: Fairness audits are increasingly mandated in high-stakes applications such as hiring, lending, and automated decision-making. Recent work has establishe

Fairness in Augmented Graph Learning: A Survey

arXiv:2504.21296v2 Announce Type: replace Abstract: Graph learning has evolved into Augmented Graph Learning (AGL) by integrating specialized machine learning (ML) techniques. Examples include federat

FineMoLA: Towards Fine-Grained Motion-Language Alignment from Clip-Level Supervision

arXiv:2608.01392v1 Announce Type: new Abstract: Text-conditioned human motion generation has made rapid progress with the emergence of large-scale motion--language datasets. However, even datasets wit

From AI Weather Prediction to Infrastructure Resilience: A Real-Time Correction-Downscaling Framework for Tropical Cyclone Impact Forecasting

arXiv:2603.12828v2 Announce Type: replace-cross Abstract: This paper addresses a missing capability in infrastructure resilience: turning fast, global AI weather forecasts into asset-scale, actionable

FusionRS: A Large-Scale RGB-Infrared-Style Remote Sensing Dataset for Cross-Modal Vision-Language Learning

arXiv:2606.17020v2 Announce Type: replace Abstract: Remote sensing vision-language models have advanced Earth observation, but available large-scale vision-language resources remain RGB-centered, leav

GAPSL: A Gradient-Aligned Parallel Split Learning over Data-Heterogeneous Edge Computing Systems

arXiv:2603.18540v2 Announce Type: replace Abstract: The increasing complexity of neural networks poses significant challenges for democratizing federated learning (FL) on resource-constrained edge dev

GenTrack: Physical Alignment for Robot-Native Motion Generation and Zero-Shot Humanoid Tracking

arXiv:2608.01410v1 Announce Type: cross Abstract: General-purpose humanoid trackers can execute diverse references, but their zero-shot coverage depends on large embodied corpora that are costly to ex

GeoArbiter: Verifiability-Guided Grounding for Remote-Sensing Multimodal LLMs

arXiv:2608.00877v1 Announce Type: new Abstract: Remote-sensing multimodal large language models (MLLMs) often assert facts that imagery cannot establish, such as a facility's identity or function. Coo

Hermite Curves as Trajectory Priors for Vision-Language-Action Models

arXiv:2608.01265v1 Announce Type: cross Abstract: Despite recent progress in Vision-Language-Action (VLA) models for robotic manipulation, the action chunk remains a weakly structured interface. Exist

Heterogeneous Multi-Agent Reinforcement Learning for Radio Resource Management under Coupled Finite-Horizon Constraints

arXiv:2608.01745v1 Announce Type: new Abstract: Maximizing throughput under proportional fairness in dense wireless networks requires jointly managing user association, scheduling, base station (BS) a

Hierarchical Pre-Training of Vision Encoders with Large Language Model

arXiv:2604.00086v2 Announce Type: replace-cross Abstract: The field of computer vision has experienced significant advancements through scalable vision encoders and multimodal pre-training frameworks.

Human-LLM Alignment in Language Attitudes Toward Non-Native Japanese

arXiv:2608.01629v1 Announce Type: new Abstract: Large language models (LLMs) increasingly evaluate human writing in high-stakes domains such as hiring and academic assessment, putting non-native speak

Hybrid-Domain Posterior Sampling for Inverse Problems via Latent Flow Matching

arXiv:2608.00537v1 Announce Type: new Abstract: Latent Flow Models have revolutionized compressed-space image synthesis, yet their application to high-fidelity inverse problems remains bottlenecked. I

IACM-RL: Intent-Aware Context Management and Reinforcement Learning for Complex Tool Invocation under Dynamic Intent Fluctuations

arXiv:2608.02110v1 Announce Type: new Abstract: Executing long-horizon tool invocations in real-world environments is severely challenged by dynamic user intent noise. Existing methods attempt robustn

Inference-Time Policy Alignment for Fair Reinforcement Learning

arXiv:2608.00175v1 Announce Type: new Abstract: Deep reinforcement learning (RL) agents achieve strong performance by optimizing scalar reward functions. However, once deployed, the policies of these

Instruction-Conditioned Exploration with Asymmetric Reinforcement Learning and Self-Distillation

arXiv:2608.02087v1 Announce Type: cross Abstract: Post-training Large Language Models (LLMs) with Reinforcement Learning (RL) has become an important tool for improving model capabilities, but the LLM

Investigating Social Bias in Narrative Image Generation

arXiv:2608.01780v1 Announce Type: new Abstract: Text-to-image (T2I) generation models are increasingly embedded in applications such as media content creation and education, raising concerns about how

LAB-Tab: LLM-Augmented Bayesian Network Adaptation for Few-Shot Tabular Generation

arXiv:2608.01879v1 Announce Type: new Abstract: Tabular data generation supports analysis and decision-making when target-domain data are scarce, yet collecting complete target samples is often costly

Latent-Regime Bias Auditing for Volatility Forecasting

arXiv:2608.01599v1 Announce Type: new Abstract: Volatility forecasts are commonly evaluated with aggregate accuracy metrics such as RMSE and MAE, but these metrics can hide conditional failures that m

LEAP: Lean Environment-Feedback via Adaptive Pruning for Code RL in GPU Kernel Generation

arXiv:2608.01804v1 Announce Type: new Abstract: Post-training large language models (LLMs) via reinforcement learning (RL) has significantly advanced code generation capabilities. To bypass the heavy

Learning-Based Collaborative MEC for LLM Inference with Soft-Deadline Awareness via Transformer-Enhanced PPO

arXiv:2608.02031v1 Announce Type: cross Abstract: This paper investigates collaborative mobile edge computing (MEC) servers for large language model (LLM) inference under soft deadline constraints. In

Learning-Based Stochastic Optimal Control with Infinite-Horizon Probabilistic Constraints

arXiv:2608.01151v1 Announce Type: cross Abstract: In this paper, we consider stochastic optimal control problems with infinite-horizon joint chance constraints. By means of an appropriate state augmen

Learning How Much, Not Just What: Cross-Patient Burden Order for CT Vision-Language Pretraining

arXiv:2608.00231v1 Announce Type: new Abstract: Volumetric CT vision-language pretraining learns 3D representations from scan-report pairs, but global and anatomy-aware objectives supervise only corre

Learning Not to Optimize: Physics-Informed Action-Space Reshaping for Intent-Based Network Control

arXiv:2608.00908v1 Announce Type: cross Abstract: Modern network policy control maps intent to sequential placement-control decisions. Bellman-style policy optimization primarily asks which action to

Learning Panorama-Aware VLA for Mobile Manipulation with Whole-Body Teleoperation

arXiv:2608.02257v1 Announce Type: new Abstract: Mobile manipulation is a key capability for embodied intelligence, enabling robots to accomplish complex multi-stage tasks in open-world environments. H

Learning to See Locally and Align Clinically with Pathology Semantics for Radiology Report Generation

arXiv:2608.00279v1 Announce Type: cross Abstract: Recent radiology-adapted vision-language models have achieved strong performance on standard report generation benchmarks, yet their robustness and ge

LLM-OSDA: An Optimal-Stopping Dynamic Auction for Native Advertising in Multi-Turn LLM Conversations

arXiv:2608.00123v1 Announce Type: new Abstract: LLM-native advertising embeds sponsored content directly into model-generated responses, shifting the unit of sale from a fixed slot to a moment within

LM-mixup: Text Data Augmentation via Language Model based Mixup

arXiv:2510.20449v2 Announce Type: replace Abstract: Instruction tuning is crucial for aligning Large Language Models (LLMs), yet the quality of instruction-following data varies significantly. While h