Search: “safety”

Unlocking Proactivity in Task-Oriented Dialogue

arXiv:2605.22240v2 Announce Type: replace Abstract: Proactive task-oriented dialogue (TOD), such as outbound sales, demands a persuasive agent that actively probes the user's concerns and steers the c

Value Entanglement: Conflation Between Different Kinds of Good In (Some) Large Language Models

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

DGX agent

arXiv:2602.19101v2 Announce Type: replace-cross Abstract: Value alignment of Large Language Models (LLMs) requires us to empirically measure these models' actual, acquired representation of value. Amo

safetyarxiv-cs-ai

4 Jun 2026

VentAgent: When LLMs Learn to Breathe -- Multi-Objective Arbitration for ARDS Ventilation

arXiv:2606.04632v1 Announce Type: cross Abstract: Mechanical ventilation for Acute Respiratory Distress Syndrome (ARDS) requires balancing competing physiological goals, including oxygenation, lung pr

VT-3DAD: Cross-Category 3D Anomaly Detection via Visual-Text Normal Space Alignment

arXiv:2606.04369v1 Announce Type: new Abstract: Few-shot cross-category 3D anomaly detection aims to determine whether an unknown point cloud belongs to a target normal category using only a few norma

safetyarxiv-cs-cv

WAM-Nav: Asymmetric Latent World-Action Modeling for Unified Visual Navigation

arXiv:2606.04907v1 Announce Type: new Abstract: Visual navigation requires generating smooth and collision-free trajectories under complex geometric and physical constraints. Existing reactive policie

What Type of Inference is Active Inference?

arXiv:2606.04935v1 Announce Type: new Abstract: Active inference casts decision-making as inference, with the Expected Free Energy (EFE) unifying goal-directed and information-seeking behavior. Recent

When Both Layers Learn: Training Dynamics of Representing Linear Models via ReLU Networks

arXiv:2606.04476v1 Announce Type: new Abstract: In this paper, we study the gradient descent dynamics for jointly training both layers of a one-hidden-layer ReLU network to fit a linear target functio

X4Val: Learning Neural Surrogates for Variance-Reduced Policy Evaluation

arXiv:2606.05159v1 Announce Type: new Abstract: Rigorous evaluation of learning-based robotic systems is an essential prerequisite for deployment. However, real-world test data is expensive to gather;

ZeroWBC: Learning Natural Whole-Body Humanoid Interaction from Human Egocentric Data

arXiv:2603.09170v2 Announce Type: replace-cross Abstract: Achieving versatile and natural whole-body humanoid interaction control remains challenging due to the high cost of whole-body teleoperation d

A Cartesian-3j Framework for Machine Learning Interatomic Potentials

arXiv:2512.16882v2 Announce Type: replace-cross Abstract: Machine learning interatomic potentials (MLIPs) have brought substantial gains in the extrapolation capability in computational chemistry. How

A Negative Result on Cross-Model Activation Transfer in a Pythia Multi-Hop Setting

arXiv:2606.03280v1 Announce Type: new Abstract: Recent work shows that language models can transmit behavioural traits through hidden signals in generated data during training. We ask whether a more d

A Pocket Offline Model for Simultaneous Speech Translation as CUNI Submission to IWSLT 2026

arXiv:2606.03948v1 Announce Type: new Abstract: We implement simultaneous translation capability with the offline direct speech-to-text translation model Canary, using the state-of-the-art policy Alig

Adaptive Causal Alignment for High-Confidence Adversarial Training

arXiv:2606.03925v1 Announce Type: new Abstract: Inverse adversarial training leverages high-confidence predictions to stabilize robust learning, yet we uncover a critical paradox: high confidence ofte

safetyarxiv-cs-cv

AirDreamer: Generalist Drone Navigation with World Models

arXiv:2606.03252v1 Announce Type: cross Abstract: Navigating a drone in unseen and cluttered environments requires reliable generalization to unseen scene layouts and understanding of environmental st

Aletheia: What Makes RLVR For Code Verifiers Tick?

arXiv:2601.12186v3 Announce Type: replace-cross Abstract: Multi-domain thinking verifiers trained via Reinforcement Learning with Verifiable Rewards (RLVR) are a cornerstone of modern post-training. H

Align-KD: Distilling Cross-Modal Alignment Knowledge for Mobile Vision-Language Model Enhancement

arXiv:2412.01282v2 Announce Type: replace-cross Abstract: Vision-Language Models (VLMs) bring powerful understanding and reasoning capabilities to multimodal tasks. Meanwhile, the great need for capab

Aligning Data-Driven Predictors with Allocation: A Decision-Focused Approach to Survival Analysis

arXiv:2606.02671v1 Announce Type: cross Abstract: Machine learning predictors have become essential tools for guiding automated decision making. However, a major misalignment persists: predictive mode

Alignment-Aware Decoding

arXiv:2509.26169v2 Announce Type: replace Abstract: Alignment of large language models remains a central challenge in natural language processing. Preference optimization has emerged as a popular and

Are we really tilting? The mechanics of reward guidance in flow and diffusion models

arXiv:2606.02884v1 Announce Type: cross Abstract: Reward guidance algorithms steer a learned generative process toward the reward-tilted measure at inference time. While empirically powerful, these me

ASAP: Exploiting the Satisficing Generalization Edge in Neural Combinatorial Optimization

arXiv:2501.17377v4 Announce Type: replace-cross Abstract: Deep Reinforcement Learning (DRL) has emerged as a promising approach for solving Combinatorial Optimization (CO) problems, such as the 3D Bin

ASymPO: Asymmetric-Scale Policy Optimization for Asynchronous LLM Post-Training Without Behavior Information

arXiv:2606.03070v1 Announce Type: cross Abstract: Asynchronous reinforcement learning can improve language-model post-training throughput by decoupling response generation from policy optimization, bu

Attention Calibration for Position-Fair Dense Information Retrieval

arXiv:2606.02737v1 Announce Type: cross Abstract: Dense retrieval models exhibit positional bias: retrieval effectiveness degrades when relevant information appears later in a passage (Zeng et al., 20

Bayesian Tensor Decomposition with Diffusion Model Prior

arXiv:2606.03212v1 Announce Type: new Abstract: Low-rank tensor decomposition (TD) is usually effective on clean, fully observed data, but it often degrades under severe missingness or noise. Low-rank

Best of Both Worlds: Multimodal Reasoning and Generation via Unified Discrete Flow Matching

arXiv:2602.12221v2 Announce Type: replace Abstract: We propose UniDFlow, a unified discrete flow-matching framework for multimodal understanding, generation, and editing. It decouples understanding an

safetyarxiv-cs-cv

Bionic Human-Motion Style Transfer for Physically Executable Whole-Body Control of Humanoid Robots

arXiv:2606.03536v1 Announce Type: new Abstract: Expressive whole-body motion is important for humanoid robots operating in human environments, where robots are expected to move stably while presenting

Black-box, Adaptive, Efficient, Transferable, Harmful, Applicable... Attacks Are All You Need to Break LLMs

arXiv:2606.03647v1 Announce Type: cross Abstract: Accurately evaluating adversarial robustness is a longstanding challenge. A flawed attack design can inflate robustness estimates, making deployment r

Breaking the Self-Confirming Loop: Diagnosing and Mitigating Systemic Reward Bias in Self-Rewarding RL

arXiv:2510.08977v2 Announce Type: replace-cross Abstract: Reinforcement learning with verifiable rewards (RLVR) efficiently scales the reasoning ability of large language models (LLMs) but is bottlene

Brief Announcement: Generative Markov Model for Distributed Computing Systems

arXiv:2606.03061v1 Announce Type: cross Abstract: Emerging distributed computing paradigms, such as the computing continuum, are inherently heterogeneous, stochastic, and complex. Efficiently and effe

Building Better Activation Oracles

arXiv:2606.02609v1 Announce Type: cross Abstract: Activation Oracles (AOs) are promising methods for interpreting residual stream activations. However, current AOs face important issues, such as hallu

Coherence Maximization Improves Pluralistic Alignment

arXiv:2606.03110v1 Announce Type: new Abstract: Aligning AI systems with diverse human values requires value specifications grounded in concrete examples, but generating such examples without extensiv

Collab-REC: An LLM-based Agentic Framework for Balancing Recommendations in Tourism

arXiv:2508.15030v5 Announce Type: replace Abstract: We propose COLLAB-REC, a multi-agent framework designed to counteract popularity bias and improve diversity in tourism recommendations. In our setup

Consistency Training Can Entrench Misalignment

arXiv:2606.03810v1 Announce Type: cross Abstract: Consistency training encourages a model to produce similar outputs across related inputs or sampling procedures. Such methods are simple, scalable, an

ConTrack: Constrained Hand Motion Tracking with Adaptive Trade-off Control

arXiv:2606.03177v1 Announce Type: new Abstract: Human demonstrations provide strong priors for robot manipulation, yet it is non-trivial to transfer them to execute on real robots due to the kinematic

ConTraIRL: Factorized Contrastive Abstractions for Transferable IRL

arXiv:2606.03017v1 Announce Type: cross Abstract: Reward transfer in Inverse Reinforcement Learning (IRL) is unreliable when policies must generalize to unseen combinations of environment dynamics and

Contrastive Neural Algorithmic Reasoning for Graph Coloring

arXiv:2606.03923v1 Announce Type: new Abstract: Graph coloring seeks to assigns colors to a graph's nodes so that adjacent nodes receive different colors, using as few colors as possible. Here, we stu

Correcting Neural Operator Spectral Bias via Diffusion Posterior Sampling with Sparse Observations

arXiv:2606.03936v1 Announce Type: new Abstract: Neural operator surrogates (NO) approximate PDE solutions orders of magnitude faster than numerical solvers, but suffer from spectral bias: high-frequen

CP-Agent: Context-Aware Multimodal Reasoning for Cellular Morphological Profiling under Chemical Perturbations

arXiv:2606.03435v1 Announce Type: new Abstract: Cell Painting combines multiplexed fluorescent staining, high-content imaging, and quantitative analysis to generate high-dimensional phenotypic readout

Curriculum-Adapted Robust Reinforcement Learning for UAV Deconfliction in Adversarial Environments

arXiv:2506.21129v2 Announce Type: replace-cross Abstract: Autonomous unmanned aerial vehicles (UAVs) increasingly rely on reinforcement learning (RL) for navigation. However, global navigation satelli

Data- and Variance-dependent Regret Bounds for Online Tabular MDPs

arXiv:2602.01903v2 Announce Type: replace Abstract: This work studies online episodic tabular Markov decision processes (MDPs) with known transitions and develops best-of-both-worlds algorithms that a

Denoise First, Orthogonalize Later: Understanding Momentum in Muon via Spectral Filtering

arXiv:2606.03899v1 Announce Type: new Abstract: Muon has recently demonstrated strong empirical performance in large language model training, but the theoretical role of momentum in Muon remains uncle

Denoising Tells When to Replan: Denoising-Variance Adaptive Chunking for Flow-Based Robot Policies

arXiv:2606.03847v1 Announce Type: new Abstract: Action chunking has become a common inference strategy for flow-based robot policies, improving action coherence by modeling multi-step temporal depende

Discovering autonomous quantum error correction via deep reinforcement learning

arXiv:2511.12482v2 Announce Type: replace-cross Abstract: Quantum error correction is essential for fault-tolerant quantum computing. However, standard methods relying on active measurements may intro

Do Explanations Increase the Risk of Decision Logic Leakage? Explanation-Guided Stealing of Graph Models

arXiv:2506.03087v2 Announce Type: replace-cross Abstract: Graph Neural Networks (GNNs) have become essential tools for analyzing graph-structured data in domains such as drug discovery and financial a

Do Neural Retrievers Prefer Certain Documents? Evidence of Learned Relevance Priors

arXiv:2606.02814v1 Announce Type: cross Abstract: Neural retrievers are trained to estimate query-document relevance from annotated query-document pairs. Yet annotation protocols may not purely reflec

DriftSched: Adaptive QoS-Aware Scheduling under Runtime Token Drift for Multi-Tenant GPU Inference

arXiv:2606.02982v1 Announce Type: cross Abstract: The rapid growth of large language model (LLM) inference services has increased the demand for efficient multi-tenant GPU scheduling. While modern inf

Dynamic Short Convolutions Improve Transformers

arXiv:2606.03825v1 Announce Type: cross Abstract: Transformers have become the dominant architecture for large language models, largely due to the scalability and flexibility of attention, feed-forwar

Effect of Demographic Bias on Skin Lesion Classification

arXiv:2606.03214v1 Announce Type: new Abstract: In this study, we evaluate the performance of skin lesion classification using ResNet-based convolutional models, focusing on the impact of demographic

Entropy Is Not Enough: Unlocking Effective Reinforcement Learning for Visual Reasoning via Vision-Anchored Token Selection

arXiv:2606.03937v1 Announce Type: new Abstract: While token-level entropy is commonly recognized as effective for credit assignment in text-only reinforcement learning with verifiable rewards (RLVR),