Search: “safety”

Learning to count small and clustered objects with application to bacterial colonies

arXiv:2604.20030v1 Announce Type: new Abstract: Automated bacterial colony counting from images is an important technique to obtain data required for the development of vaccines and antibiotics. Howev

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Lever: Inference-Time Policy Reuse under Support Constraints

DGX agent

arXiv:2604.20174v1 Announce Type: new Abstract: Reinforcement learning (RL) policies are typically trained for fixed objectives, making reuse difficult when task requirements change. We study inferenc

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23 Apr 2026

LLM Agents Predict Social Media Reactions but Do Not Outperform Text Classifiers: Benchmarking Simulation Accuracy Using 120K+ Personas of 1511 Humans

arXiv:2604.19787v1 Announce Type: cross Abstract: Social media platforms mediate how billions form opinions and engage with public discourse. As autonomous AI agents increasingly participate in these

MATT-Diff: Multimodal Active Target Tracking by Diffusion Policy

arXiv:2511.11931v2 Announce Type: replace Abstract: This paper proposes MATT-Diff: Multimodal Active Target Tracking by Diffusion Policy, a control policy for active multi-target tracking using a mobi

Membership Inference for Contrastive Pre-training Models with Text-only PII Queries

arXiv:2603.14222v2 Announce Type: replace-cross Abstract: Contrastive pretraining models such as CLIP and CLAP, serve as the ubiquitous perceptual backbones for modern multimodal large models, yet the

Memorization, Emergence, and Explaining Reversal Failures: A Controlled Study of Relational Semantics in LLMs

arXiv:2601.02931v2 Announce Type: replace Abstract: Autoregressive LLMs perform well on relational tasks that require linking entities via relational words (e.g., father/son, friend), but it is unclea

MOA: Multi-Objective Alignment for Role-Playing Agents

arXiv:2512.09756v2 Announce Type: replace Abstract: Role-playing agents (RPAs) require balancing multiple objectives, such as instruction following, persona consistency, and stylistic fidelity, which

Multi-Armed Bandits With Machine Learning-Generated Surrogate Rewards

arXiv:2506.16658v2 Announce Type: replace-cross Abstract: Multi-armed bandit (MAB) is a widely adopted framework for sequential decision-making under uncertainty. Traditional bandit algorithms rely so

Multi-Objective Reinforcement Learning for Generating Covalent Inhibitor Candidates

arXiv:2604.20019v1 Announce Type: new Abstract: Rational design of covalent inhibitors requires simultaneously optimizing multiple properties, such as binding affinity, target selectivity, or electrop

Near-Future Policy Optimization

arXiv:2604.20733v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) has become a core post-training recipe. Introducing suitable off-policy trajectories into on-polic

Occupancy Reward Shaping: Improving Credit Assignment for Offline Goal-Conditioned Reinforcement Learning

arXiv:2604.20627v1 Announce Type: new Abstract: The temporal lag between actions and their long-term consequences makes credit assignment a challenge when learning goal-directed behaviors from data. G

ORPHEAS: A Cross-Lingual Greek-English Embedding Model for Retrieval-Augmented Generation

arXiv:2604.20666v1 Announce Type: cross Abstract: Effective retrieval-augmented generation across bilingual Greek--English applications requires embedding models capable of capturing both domain-speci

Participatory provenance as representational auditing for AI-mediated public consultation

arXiv:2604.20711v1 Announce Type: new Abstract: Artificial intelligence is increasingly deployed to synthesize large-scale public input in policy consultations and participatory processes. Yet no form

Model Releases

Peer-Preservation in Frontier Models

model-releasesarxiv-cs-ai

arXiv:2604.19784v1 Announce Type: cross Abstract: Recently, it has been found that frontier AI models can resist their own shutdown, a behavior known as self-preservation. We extend this concept to th

ProMMSearchAgent: A Generalizable Multimodal Search Agent Trained with Process-Oriented Rewards

arXiv:2604.20486v1 Announce Type: new Abstract: Training multimodal agents via reinforcement learning for knowledge-intensive visual reasoning is fundamentally hindered by the extreme sparsity of outc

Recency Biased Causal Attention for Time-series Forecasting

arXiv:2502.06151v2 Announce Type: replace-cross Abstract: Recency bias is a useful inductive prior for sequential modeling: it emphasizes nearby observations and can still allow longer-range dependenc

Relative Principals, Pluralistic Alignment, and the Structural Value Alignment Problem

arXiv:2604.20805v1 Announce Type: cross Abstract: The value alignment problem for artificial intelligence (AI) is often framed as a purely technical or normative challenge, sometimes focused on hypoth

Representational Alignment Across Model Layers and Brain Regions with Multi-Level Optimal Transport

arXiv:2510.01706v2 Announce Type: replace-cross Abstract: Standard representational similarity methods align each layer of a network to its best match in another independently, producing asymmetric re

Rethinking Reinforcement Fine-Tuning in LVLM: Convergence, Reward Decomposition, and Generalization

arXiv:2604.19857v1 Announce Type: cross Abstract: Reinforcement fine-tuning with verifiable rewards (RLVR) has emerged as a powerful paradigm for equipping large vision-language models (LVLMs) with ag

Rodrigues Network for Learning Robot Actions

arXiv:2506.02618v2 Announce Type: replace-cross Abstract: Understanding and predicting articulated actions is important in robot learning. However, common architectures such as MLPs and Transformers l

Sampling-Aware Quantization for Diffusion Models

arXiv:2505.02242v2 Announce Type: replace Abstract: Diffusion models have recently emerged as the dominant approach in visual generation tasks. However, the lengthy denoising chains and the computatio

SignDATA: Data Pipeline for Sign Language Translation

arXiv:2604.20357v1 Announce Type: cross Abstract: Sign-language datasets are difficult to preprocess consistently because they vary in annotation schema, clip timing, signer framing, and privacy const

Storm Surge Modeling, Bias Correction, Graph Neural Networks, Graph Convolution Networks

arXiv:2604.20688v1 Announce Type: cross Abstract: Storm surge forecasting remains a critical challenge in mitigating the impacts of tropical cyclones on coastal regions, particularly given recent tren

Temporal Difference Calibration in Sequential Tasks: Application to Vision-Language-Action Models

arXiv:2604.20472v1 Announce Type: cross Abstract: Recent advances in vision-language-action (VLA) models for robotics have highlighted the importance of reliable uncertainty quantification in sequenti

The Existential Theory of Research: Why Discovery Is Hard

arXiv:2604.19810v1 Announce Type: new Abstract: Can scientific discovery be made arbitrarily easy by choosing the right representation, collecting enough data, and deploying sufficiently powerful algo

The Imperfective Paradox in Large Language Models

arXiv:2601.09373v2 Announce Type: replace Abstract: Do Large Language Models (LLMs) genuinely grasp the compositional semantics of events, or do they rely on surface-level probabilistic heuristics? We

The Tool-Overuse Illusion: Why Does LLM Prefer External Tools over Internal Knowledge?

arXiv:2604.19749v1 Announce Type: new Abstract: Equipping LLMs with external tools effectively addresses internal reasoning limitations. However, it introduces a critical yet under-explored phenomenon

Throat and acoustic paired speech dataset for deep learning-based speech enhancement

arXiv:2502.11478v3 Announce Type: replace-cross Abstract: In high-noise environments such as factories, subways, and busy streets, capturing clear speech is challenging. Throat microphones can offer a

Understanding Overparametrization in Survival Models through Interpolation

arXiv:2512.12463v3 Announce Type: replace-cross Abstract: Classical statistical learning theory predicts a U-shaped relationship between test loss and model capacity, driven by the bias-variance trade

UVIO: An UWB-Aided Visual-Inertial Odometry Framework with Bias-Compensated Anchors Initialization

arXiv:2308.00513v2 Announce Type: replace Abstract: This paper introduces UVIO, a multi-sensor framework that leverages Ultra Wide Band (UWB) technology and Visual-Inertial Odometry (VIO) to provide r

V-tableR1: Process-Supervised Multimodal Table Reasoning with Critic-Guided Policy Optimization

arXiv:2604.20755v1 Announce Type: new Abstract: We introduce V-tableR1, a process-supervised reinforcement learning framework that elicits rigorous, verifiable reasoning from multimodal large language

Visual-Tactile Peg-in-Hole Assembly Learning from Peg-out-of-Hole Disassembly

arXiv:2604.20712v1 Announce Type: new Abstract: Peg-in-hole (PiH) assembly is a fundamental yet challenging robotic manipulation task. While reinforcement learning (RL) has shown promise in tackling s

What Makes a Good AI Review? Concern-Level Diagnostics for AI Peer Review

arXiv:2604.19998v1 Announce Type: new Abstract: Evaluating AI-generated reviews by verdict agreement is widely recognized as insufficient, yet current alternatives rarely audit which concerns a system

Where and What: Reasoning Dynamic and Implicit Preferences in Situated Conversational Recommendation

arXiv:2604.20749v1 Announce Type: new Abstract: Situated conversational recommendation (SCR), which utilizes visual scenes grounded in specific environments and natural language dialogue to deliver co

Which Reasoning Trajectories Teach Students to Reason Better? A Simple Metric of Informative Alignment

arXiv:2601.14249v4 Announce Type: replace Abstract: Long chain-of-thought (CoT) trajectories provide rich supervision signals for distilling reasoning from teacher to student LLMs. However, both prior

Whose Story Gets Told? Positionality and Bias in LLM Summaries of Life Narratives

arXiv:2604.20131v1 Announce Type: new Abstract: Increasingly, studies are exploring using Large Language Models (LLMs) for accelerated or scaled qualitative analysis of text data. While we can compare

Working Memory Constraints Scaffold Learning in Transformers under Data Scarcity

arXiv:2604.20789v1 Announce Type: cross Abstract: We investigate the integration of human-like working memory constraints into the Transformer architecture and implement several cognitively inspired a

Adaptive Prompt Elicitation for Text-to-Image Generation

arXiv:2602.04713v2 Announce Type: replace-cross Abstract: Aligning text-to-image generation with user intent remains challenging, as users frequently provide ambiguous inputs and struggle with model i

AeroBridge-TTA: Test-Time Adaptive Language-Conditioned Control for UAVs

arXiv:2604.19059v1 Announce Type: new Abstract: Language-guided unmanned aerial vehicles (UAVs) often fail not from bad reasoning or perception, but from execution mismatch: the gap between a planned

AlignedCut: Visual Concepts Discovery on Brain-Guided Universal Feature Space

arXiv:2406.18344v2 Announce Type: replace Abstract: We study the intriguing connection between visual data, deep networks, and the brain. Our method creates a universal channel alignment by using brai

Allo{SR}^2: Rectifying One-Step Super-Resolution to Stay Real via Allomorphic Generative Flows

arXiv:2604.19238v1 Announce Type: new Abstract: Real-world image super-resolution (Real-SR) has been revolutionized by leveraging the powerful generative priors of large-scale diffusion and flow-based

ARM: Advantage Reward Modeling for Long-Horizon Manipulation

arXiv:2604.03037v2 Announce Type: replace-cross Abstract: Long-horizon robotic manipulation remains challenging for reinforcement learning (RL) because sparse rewards provide limited guidance for cred

Attention-based Multi-modal Deep Learning Model of Spatio-temporal Crop Yield Prediction with Satellite, Soil and Climate Data

arXiv:2604.19217v1 Announce Type: cross Abstract: Crop yield prediction is one of the most important challenge, which is crucial to world food security and policy-making decisions. The conventional fo

Auditing LLMs for Algorithmic Fairness in Casenote-Augmented Tabular Prediction

arXiv:2604.19204v1 Announce Type: cross Abstract: LLMs are increasingly being considered for prediction tasks in high-stakes social service settings, but their algorithmic fairness properties in this

Beyond Bellman: High-Order Generator Regression for Continuous-Time Policy Evaluation

arXiv:2604.18972v1 Announce Type: cross Abstract: We study finite-horizon continuous-time policy evaluation from discrete closed-loop trajectories under time-inhomogeneous dynamics. The target value s

Beyond Marginal Distributions: A Framework to Evaluate the Representativeness of Demographic-Aligned LLMs

arXiv:2601.15755v3 Announce Type: replace Abstract: Large language models are increasingly used to represent human opinions, values, or beliefs, and their steerability towards these ideals is an activ

Beyond the Bellman Fixed Point: Geometry and Fast Policy Identification in Value Iteration

arXiv:2604.17457v2 Announce Type: replace-cross Abstract: Dynamic programming is one of the most fundamental methodologies for solving Markov decision problems. Among its many variants, Q-value iterat

Breaking the Illusion: Consensus-Based Generative Mitigation of Adversarial Illusions in Multi-Modal Embeddings

arXiv:2511.21893v2 Announce Type: replace Abstract: Multi-modal foundation models align images, text, and other modalities in a shared embedding space but remain vulnerable to adversarial illusions [3