Search: “concepts”

Retrieval-Guided Generation for Safer Histopathology Image Captioning

arXiv:2605.00893v1 Announce Type: new Abstract: Generative vision-language models can produce fluent medical image captions but remain prone to hallucination, over-specific diagnostic claims, and fact

safetyarxiv-cs-cv

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Retrieval with Multiple Query Vectors through Anomalous Pattern Detection

DGX agent

arXiv:2605.01965v1 Announce Type: new Abstract: A classical vector retrieval problem typically considers a single query embedding vector as input and retrieves the most similar embedding vectors from

researcharxiv-cs-lg

5 May 2026

ROBOPOL: Social Robotics Meets Vehicular Communications for Cooperative Automated Driving

arXiv:2512.24129v2 Announce Type: replace Abstract: On the way toward full autonomy, sharing roads between automated and autonomous vehicles in so-called mixed traffic is unavoidable. Moreover, even i

agentsarxiv-cs-ro

SRA: Span Representation Alignment for Large Language Model Distillation

arXiv:2605.01205v1 Announce Type: new Abstract: Cross-Tokenizer Knowledge Distillation (CTKD) enables knowledge transfer between a large language model and a smaller student, even when they employ dif

safetyarxiv-cs-cl

Applications

The grip of grammar on meaning uncertainty: cross-linguistic evidence, neural correlates, and clinical relevance

arXiv:2605.01537v1 Announce Type: new Abstract: Isolated word meanings are inherently uncertain. This uncertainty reduces when they are combined and anchored in context. We propose that grammar compre

applicationsarxiv-cs-cl

The Pragmatic Frames of Spurious Correlations in Machine Learning: Interpreting How and Why They Matter

arXiv:2411.04696v5 Announce Type: replace Abstract: Learning correlations from data forms the foundation of today's machine learning (ML) and artificial intelligence research. While contemporary metho

Turning Drift into Constraint: Robust Reasoning Alignment in Non-Stationary Environments

arXiv:2510.04142v2 Announce Type: replace Abstract: This paper identifies a critical yet underexplored challenge in reasoning alignment from multiple multi-modal large language models (MLLMs): In non-

Unbox Responsible GeoAI: Navigating Climate Extreme and Disaster Mapping

arXiv:2605.00315v1 Announce Type: cross Abstract: As climate extreme and disaster events become more frequent and intense, Geospatial Artificial Intelligence (GeoAI) has emerged as a transformative ap

Gradient Regularized Newton Boosting Trees with Global Convergence

arXiv:2605.00581v1 Announce Type: cross Abstract: Gradient Boosting Decision Trees (GBDTs) dominate tabular machine learning, with modern implementations like XGBoost, LightGBM, and CatBoost being bas

researcharxiv-cs-lg

Image Score: Learning and Evaluating Human Preferences for Mercari Search

arXiv:2408.11349v2 Announce Type: replace Abstract: Mercari is the largest C2C e-commerce marketplace in Japan, having more than 20 million active monthly users. Search being the fundamental way to di

researcharxiv-cs-cv

Jailbreaking Vision-Language Models Through the Visual Modality

arXiv:2605.00583v1 Announce Type: new Abstract: The visual modality of vision-language models (VLMs) is an underexplored attack surface for bypassing safety alignment. We introduce four jailbreak atta

On the Role of Artificial Intelligence in Human-Machine Symbiosis

arXiv:2605.00440v1 Announce Type: cross Abstract: The evolution of artificial intelligence (AI) has rendered the boundary between humanity and computational machinery increasingly ambiguous. In the pr

agentsarxiv-cs-cl

Reinforcement Learning with Markov Risk Measures and Multipattern Risk Approximation

arXiv:2605.00654v1 Announce Type: new Abstract: For a risk-averse finite-horizon Markov Decision Problem, we introduce a special class of Markov coherent risk measures, called mini-batch measures. We

Representation in large language models

arXiv:2501.00885v2 Announce Type: replace Abstract: The extraordinary success of recent Large Language Models (LLMs) on a diverse array of tasks has led to an explosion of scientific and philosophical

researcharxiv-cs-cl

Statistical Testing Framework for Clustering Pipelines by Selective Inference

arXiv:2603.18413v3 Announce Type: replace-cross Abstract: A data analysis pipeline is a structured sequence of steps that transforms raw data into meaningful insights by integrating multiple analysis

researcharxiv-cs-lg

AesRM: Improving Video Aesthetics with Expert-Level Feedback

arXiv:2604.28078v1 Announce Type: new Abstract: Despite rapid advances in photorealistic video generation, real-world applications such as filmmaking require video aesthetics, e.g., harmonious colors

Applications

Context as Prior: Bayesian-Inspired Intent Inference for Non-Speaking Agents with a Household Cat Testbed

arXiv:2604.27445v1 Announce Type: new Abstract: Many agents in real-world environments cannot reliably communicate their goals through language, including household pets, pre-verbal infants, and other

applicationsarxiv-cs-cv

Local Ai

Effective Prompt Pool Learning for Continual Category Discovery

arXiv:2407.19001v3 Announce Type: replace Abstract: This paper studies effective prompt pool learning for Continual Category Discovery (CCD), a challenging open-world setting where a model must discov

local-aiarxiv-cs-cv

Evaluating Epistemic Guardrails in AI Reading Assistants: A Behavioral Audit of a Minimal Prototype

arXiv:2604.27275v1 Announce Type: cross Abstract: Large language model (LLM) reading assistants are increasingly used in settings that require interpretation rather than simple retrieval. In these con

Fake3DGS: A Benchmark for 3D Manipulation Detection in Neural Rendering

arXiv:2604.27590v1 Announce Type: new Abstract: Recent advances in 3D reconstruction and neural rendering,particularly 3D Gaussian Splatting, make it feasible and simple to edit 3D scenes and re-rende

Junk DNA Hypothesis: Pruning Small Pre-Trained Weights Irreversibly and Monotonically Impairs 'Difficult' Downstream Tasks in LLMs

arXiv:2310.02277v4 Announce Type: replace-cross Abstract: We present Junk DNA Hypothesis by adopting a novel task-centric angle for the pre-trained weights of large language models (LLMs). It has been

Knowledge Affordances for Hybrid Human-AI Information Seeking

arXiv:2604.27539v1 Announce Type: cross Abstract: As information ecosystems grow more heterogeneous, both humans and artificial agents increasingly face a simple yet unresolved question: when seeking

agentsarxiv-cs-ai

Learning-Based Hierarchical Scene Graph Matching for Robot Localization Leveraging Prior Maps

arXiv:2604.27821v1 Announce Type: new Abstract: Accurate localization is a fundamental requirement for autonomous robots operating in indoor environments. Scene graphs encode the spatial structure of

agentsarxiv-cs-ro

Math Education Digital Shadows for facilitating learning with LLMs: Math performance, anxiety and confidence in simulated students and AIs

arXiv:2604.27618v1 Announce Type: new Abstract: To enhance LLMs' impact on math education, we need data on their mathematical prowess and biases across prompts. To fill this gap, we introduce MEDS (Ma

Not All Memories Age the Same: Autodiscovery of Adaptive Decay in Knowledge Graphs

arXiv:2604.26970v1 Announce Type: cross Abstract: Knowledge graphs used for retrieval treat all facts as equally current. Existing temporal approaches apply uniform decay, using a single forgetting cu

Splitting Assumption-Based Argumentation Frameworks

arXiv:2604.27964v1 Announce Type: new Abstract: Assumption-Based Argumentation (ABA) is a well-established formalism for modelling and reasoning over debates, with a wide range of applications. Howeve

The Effects of Visual Priming on Cooperative Behavior in Vision-Language Models

arXiv:2604.27953v1 Announce Type: new Abstract: As Vision-Language Models (VLMs) become increasingly integrated into decision-making systems, it is essential to understand how visual inputs influence

safetyarxiv-cs-ai

Towards Neuro-symbolic Causal Rule Synthesis, Verification, and Evaluation Grounded in Legal and Safety Principles

arXiv:2604.28087v1 Announce Type: cross Abstract: Rule-based systems remain central in safety-critical domains but often struggle with scalability, brittleness, and goal misspecification. These limita

safetyarxiv-cs-ai

Vision-Language Models Mistake Head Orientation for Gaze Direction: Nonverbal Conversation Cues

arXiv:2506.05412v3 Announce Type: replace-cross Abstract: Where someone looks is a nonverbal communication cue that children and adults readily use. How well can Vision-Language Models (VLMs) infer ga

safetyarxiv-cs-cl

What Suppresses Nash Equilibrium Play in Large Language Models? Mechanistic Evidence and Causal Control

arXiv:2604.27167v1 Announce Type: cross Abstract: LLM agents are known to deviate from Nash equilibria in strategic interactions, but nobody has looked inside the model to understand why, or asked whe

A Survey of Multi-Agent Deep Reinforcement Learning with Graph Neural Network-Based Communication

arXiv:2604.25972v1 Announce Type: cross Abstract: In multi-agent reinforcement learning (MARL), the integration of a communication mechanism, allowing agents to better learn to coordinate their action

agentsarxiv-cs-ai

A Survey of Safe Reinforcement Learning and Constrained MDPs: A Technical Survey on Single-Agent and Multi-Agent Safety

arXiv:2505.17342v2 Announce Type: replace Abstract: Safe Reinforcement Learning (SafeRL) is the subfield of reinforcement learning that explicitly deals with safety constraints during the learning and

Deep-testing: the case of dependence detection

arXiv:2604.26558v1 Announce Type: cross Abstract: Deep learning methods have proved highly effective for classification and image recognition problems. In this paper, we ask whether this success can b

researcharxiv-cs-lg

Dynamically Extensible and Retractable Robotic Leg Linkages for Multi-task Execution in Search and Rescue Scenarios

arXiv:2511.10816v3 Announce Type: replace Abstract: Search and rescue (SAR) robots are required to quickly traverse terrain and perform high-force rescue tasks, necessitating both terrain adaptability

researcharxiv-cs-ro

Entropy Centroids as Intrinsic Rewards for Test-Time Scaling

arXiv:2604.26173v1 Announce Type: cross Abstract: An effective way to scale up test-time compute of large language models is to sample multiple responses and then select the best one, as in Grok Heavy

FunFace: Feature Utility and Norm Estimation for Face Recognition

arXiv:2604.26598v1 Announce Type: new Abstract: Face Recognition (FR) is used in a variety of application domains, from entertainment and banking to security and surveillance. Such applications rely o

researcharxiv-cs-cv

Neural-Geometric Tunnel Traversal: Localization-free UAV Flight with Tilted LiDARs

arXiv:2404.09688v2 Announce Type: replace Abstract: Navigation of UAVs in challenging environments like tunnels or mines, where it is not possible to use GNSS methods to self-localize, illumination ma

researcharxiv-cs-ro

NeuroPlastic: A Plasticity-Modulated Optimizer for Biologically Inspired Learning Dynamics

model-releasesarxiv-cs-lg

arXiv:2604.26297v1 Announce Type: new Abstract: Optimization algorithms are fundamental to modern deep learning, yet most widely used methods rely on update rules based primarily on local gradient sta

reward-lens: A Mechanistic Interpretability Library for Reward Models

arXiv:2604.26130v1 Announce Type: cross Abstract: Every RLHF-trained language model is shaped by a reward model, yet the mechanistic interpretability toolkit -- logit lens, direct logit attribution, a

Beyond Accuracy: Benchmarking Cross-Task Consistency in Unified Multimodal Models

arXiv:2604.25072v1 Announce Type: new Abstract: Unified Multimodal Models (uMMs) aim to support both visual understanding and visual generation within a shared representation. However, existing evalua

safetyarxiv-cs-cv

Bye Bye Perspective API: Lessons for Measurement Infrastructure in NLP, CSS and LLM Evaluation

arXiv:2604.25580v1 Announce Type: new Abstract: The closure of Perspective API at the end of 2026 discards what has functioned as the de facto standard for automated toxicity measurement in NLP, CSS,

researcharxiv-cs-cl

Carbon-Taxed Transformers: A Green Compression Pipeline for Overgrown Language Models

arXiv:2604.25903v1 Announce Type: cross Abstract: The accelerating adoption of Large Language Models (LLMs) in software engineering (SE) has brought with it a silent crisis: unsustainable computationa

Combating Visual Neglect and Semantic Drift in Large Multimodal Models for Enhanced Cross-Modal Retrieval

arXiv:2604.25273v1 Announce Type: new Abstract: Despite significant progress in Unified Multimodal Retrieval (UMR) powered by Large Multimodal Models (LMMs), existing embedding methods primarily focus

Local Ai

COMPASS: COmpact Multi-channel Prior-map And Scene Signature for Floor-Plan-Based Visual Localization

arXiv:2604.25388v1 Announce Type: new Abstract: Architectural floor plans are widely available priors which contain not only geometry but also the semantic information of the environment, yet existing

local-aiarxiv-cs-cv

Frontier Coding Agents Can Now Implement an AlphaZero Self-Play Machine Learning Pipeline For Connect Four That Performs Comparably to an External Solver

model-releasesarxiv-cs-lg

arXiv:2604.25067v1 Announce Type: cross Abstract: Forecasting when AI systems will become capable of meaningfully accelerating AI research is a central challenge for AI safety. Existing benchmarks mea

Learning from Medical Entity Trees: An Entity-Centric Medical Data Engineering Framework for MLLMs

arXiv:2604.25296v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have shown transformative potential in medical applications, yet their performance is hindered by conventional

safetyarxiv-cs-cl

Hardware

Practical exposure correction via compensation

arXiv:2212.14245v2 Announce Type: replace Abstract: In computer vision, correcting the exposure level is a fundamental task for enhancing the visual quality of observations with inappropriate lightnes

hardwarearxiv-cs-cv

ResetEdit: Precise Text-guided Editing of Generated Image via Resettable Starting Latent

arXiv:2604.25128v1 Announce Type: new Abstract: Recent advances in diffusion models have enabled high-quality image generation, leading to increasing demand for post-generation editing that modifies l

safetyarxiv-cs-cv