Search: “evaluation”

Individual utilities of life satisfaction reveal inequality aversion unrelated to political alignment

arXiv:2509.07793v4 Announce Type: replace-cross Abstract: How should well-being be prioritised in society, and what trade-offs are people willing to make between fairness and personal well-being? We i

safetyarxiv-cs-ai

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Research

InstructAV2AV: Instruction-Guided Audio-Video Joint Editing

DGX agent

arXiv:2605.18467v1 Announce Type: new Abstract: Recent diffusion-based methods have achieved impressive progress in video content manipulation. However, they typically ignore the accompanying audio, l

researcharxiv-cs-cv

19 May 2026

Internalizing Tool Knowledge in Small Language Models via QLoRA Fine-Tuning

model-releasesarxiv-cs-cl

arXiv:2605.17774v1 Announce Type: new Abstract: Large language models are increasingly used as planning components in agentic systems, but current tool-use pipelines often require full tool schemas to

Interpretable epistemic uncertainty decomposition in sequential generative models via polynomial chaos surrogates

arXiv:2510.21523v2 Announce Type: replace Abstract: Sequential generative models conditioned on uncertain rewards are central to AI-driven scientific discovery, yet the epistemic uncertainty they inhe

safetyarxiv-cs-lg

Tutorials

Investigating Action Encodings in Recurrent Neural Networks in Reinforcement Learning

arXiv:2605.16318v1 Announce Type: new Abstract: Building and maintaining state to learn policies and value functions is critical for deploying reinforcement learning (RL) agents in the real world. Rec

tutorialsarxiv-cs-lg

Is Complex Training Necessary for Long-Tailed OOD Detection? A Re-think from Feature Geometry

arXiv:2605.17799v1 Announce Type: new Abstract: Long-tailed out-of-distribution (LT-OOD) detection is often addressed with specialized training, including auxiliary out-of-distribution (OOD) data, abs

researcharxiv-cs-cv

Tutorials

Joint Enhancement and Classification using Coupled Diffusion Models of Signals and Logits

arXiv:2602.15405v2 Announce Type: replace Abstract: Robust classification in noisy environments remains a fundamental challenge in machine learning. Standard approaches typically treat signal enhancem

tutorialsarxiv-cs-lg

KASER: Knowledge-Aligned Student Error Simulator for Open-Ended Coding Tasks

arXiv:2601.06633v2 Announce Type: replace-cross Abstract: Open-ended tasks, such as coding problems that are common in computer science education, provide detailed insights into student knowledge. How

applicationsarxiv-cs-ai

Keeping an Eye on AI: A Framework for Effective Human Oversight of AI Systems

arXiv:2605.16278v1 Announce Type: cross Abstract: The use of Artificial Intelligence (AI) in high-risk, decision-making scenarios presents technical, safety, and normative challenges; problems that ma

safetyarxiv-cs-ai

KVCapsule: Efficient Sequential KV Cache Compression for Vision-Language Models with Asymmetric Redundancy

arXiv:2605.16439v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) have emerged as a critical and fast-growing extension of Large Language Models (LLMs) that enable multimodal reasoning t

Hardware

KVDrive: A Holistic Multi-Tier KV Cache Management System for Long-Context LLM Inference

arXiv:2605.18071v1 Announce Type: new Abstract: Supporting long-context LLMs is challenging due to the substantial memory demands of the key-value (KV) cache. Existing offloading systems store the ful

hardwarearxiv-cs-cl

Lambda’s NVIDIA HGX 8xB200 on STAC-AI™ LANG6

model-releaseslambda-labs

What the numbers mean for financial services Executive summary Lambda is the first to publish an audited STAC-AI™ LANG6 result on NVIDIA HGX 8xB200, with independently verified performance data that F

Latent Heuristic Search: Continuous Optimization for Automated Algorithm Design

arXiv:2605.17137v1 Announce Type: new Abstract: The integration of Large Language Models (LLMs) into evolutionary frameworks has established a new paradigm for automated heuristic discovery. Despite t

Learning Higher-Order Structure from Incomplete Spatiotemporal Data: Multi-Scale Hypergraph Laplacians with Neural Refinement

arXiv:2605.17316v1 Announce Type: cross Abstract: Sensor networks increasingly govern modern infrastructure, yet the data they lose are rarely missing in the uniform-random patterns assumed by standar

Learning Quantifiable Visual Explanations Without Ground-Truth

arXiv:2605.18681v1 Announce Type: new Abstract: Explainable AI (XAI) techniques are increasingly important for the validation and responsible use of modern deep learning models, but are difficult to e

Learning-Zone Energy: Online Data Selection for Efficient RL Post-Training

arXiv:2605.17003v1 Announce Type: cross Abstract: Reinforcement Learning (RL) post-training has emerged as the dominant paradigm for eliciting mathematical reasoning in Large Language Models (LLMs), y

LESSViT: Robust Hyperspectral Representation Learning under Spectral Configuration Shift

model-releasesarxiv-cs-cv

arXiv:2605.18541v1 Announce Type: new Abstract: Modeling hyperspectral imagery (HSI) across different sensors presents a fundamental challenge due to variations in wavelength coverage, band sampling,

Lever: Speculative LLM Inference on Smartphones

arXiv:2605.16786v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly needed for interactive mobile applications, but high-quality models exceed the limited DRAM available on s

researcharxiv-cs-lg

Leveraging Multimodal Self-Consistency Reasoning in Coding Motivational Interviewing for Alcohol Use Reduction

arXiv:2605.12987v2 Announce Type: replace Abstract: BACKGROUND: Coding Motivational Interviewing (MI) sessions is essential for understanding client behaviors and predicting outcomes, but it requires

researcharxiv-cs-cl

LiPS: Lightweight Panoptic Segmentation for Resource-Constrained Robotics

arXiv:2604.00634v2 Announce Type: replace-cross Abstract: Panoptic segmentation is a key enabler for robotic perception, as it unifies semantic understanding with object-level reasoning. However, the

applicationsarxiv-cs-cv

LLM-TabLogic: Preserving Inter-Column Logical Relationships in Synthetic Tabular Data via Prompt-Guided Latent Diffusion

arXiv:2503.02161v3 Announce Type: replace Abstract: Synthetic tabular data are increasingly being used to replace real data, serving as an effective solution that simultaneously protects privacy and a

applicationsarxiv-cs-lg

Local Ai

LLMs for automatic annotation of Mandarin narrative transcripts

arXiv:2605.17205v1 Announce Type: new Abstract: Linguistic annotation of transcribed speech is essential for research in language acquisition, language disorders, and sociolinguistics, yet remains lab

local-aiarxiv-cs-cl

Hardware

LogRouter: Adaptive Two-Level LLM Routing for Log Question Answering in Big Data Systems

arXiv:2605.18015v1 Announce Type: new Abstract: Production log analytics in self-hosted, resource-constrained environments requires natural-language access to massive log streams without the cost of r

hardwarearxiv-cs-lg

Lost in the Folds: When Cross-Validation Is Not a Deep Ensemble for Uncertainty Estimation

arXiv:2605.18329v1 Announce Type: new Abstract: Ensemble disagreement is widely used as a proxy for epistemic uncertainty in medical image segmentation. In practice, many studies form ensembles via K-

researcharxiv-cs-cv

LPG: Balancing Efficiency and Policy Reasoning in Latent Policy Guardrails

arXiv:2605.17329v1 Announce Type: cross Abstract: Guardrails are a critical safety layer for modern AI systems, but their operating regime is changing. As LLMs are deployed as customized assistants, s

safetyarxiv-cs-ai

LSDTs: LLM-Augmented Semantic Digital Twins for Adaptive Knowledge-Intensive Infrastructure Planning

arXiv:2508.06799v3 Announce Type: replace-cross Abstract: Digital Twins (DTs) offer powerful tools for managing complex infrastructure systems, but their effectiveness is often limited by challenges i

applicationsarxiv-cs-ai

M^2FedAQI: Multimodal Federated Learning for Air Quality Prediction on Heterogeneous Edge Devices

model-releasesarxiv-cs-lg

arXiv:2605.16375v1 Announce Type: new Abstract: Accurate air quality prediction is essential for public health, environmental monitoring, and industrial safety. However, most existing approaches rely

Agents

MA^{2}P: A Meta-Cognitive Autonomous Intelligent Agents Framework for Complex Persuasion

arXiv:2605.18572v1 Announce Type: new Abstract: Persuasive dialogue generation plays a vital role in decision-making, negotiation, counseling, and behavior change, yet it remains a challenging problem

agentsarxiv-cs-cl

MADP: A Multi-Agent Pipeline for Sustainable Document Processing with Human-in-the-Loop

arXiv:2605.17159v1 Announce Type: new Abstract: Document processing automation remains a critical challenge in enterprise environments, where traditional manual approaches are labor-intensive and erro

ManiSoft: Towards Vision-Language Manipulation for Soft Continuum Robotics

arXiv:2605.18617v1 Announce Type: cross Abstract: Most existing vision-language manipulation research targets rigid robotic arms, whose fixed morphology limits adaptability in cluttered or confined sp

Agents

MATE: Solving Contextual Markov Decision Processes with Memory of Accumulated Transition Embeddings

arXiv:2605.17431v1 Announce Type: cross Abstract: We propose MATE, a simple yet effective memory architecture for solving Contextual Markov Decision Processes (CMDPs), a family of MDPs parameterized b

agentsarxiv-cs-ai

Tutorials

Maximum Likelihood Decoding of Quantum Error Correction Codes

arXiv:2605.17230v1 Announce Type: cross Abstract: Quantum error correction (QEC) is indispensable for realizing fault-tolerant quantum computation, yet its effectiveness hinges critically on the class

tutorialsarxiv-cs-lg

Mechanism Learning: Prototype-Anchored Mechanism Inference for Scientific Forecasting

arXiv:2605.17091v1 Announce Type: new Abstract: Scientific forecasting typically relies on direct state prediction, an approach that grows brittle under data scarcity, extended horizons, non-stationar

researcharxiv-cs-lg

Medical Context Distorts Decisions in Clinical Vision Language Models

arXiv:2605.17436v1 Announce Type: cross Abstract: Vision-language models (VLMs) are increasingly proposed for clinical decision support, yet their reliability in real-world scenarios that require inte

safetyarxiv-cs-cl

Local Ai

MementoGUI: Learning Agentic Multimodal Memory Control for Long-Horizon GUI Agents

arXiv:2605.18652v1 Announce Type: new Abstract: Recent GUI agents have made substantial progress in visual grounding and action prediction, yet they remain brittle in long-horizon tasks that require m

local-aiarxiv-cs-cv

Memory-Guided Tree Search with Cross-Branch Knowledge Transfer for LLM Solver Synthesis

arXiv:2605.17539v1 Announce Type: new Abstract: Combinatorial optimization (CO) underlies decision-making from logistics to chip design, where infeasible solutions are operationally unusable and small

Agents

MemRepair: Hierarchical Memory for Agentic Repository-Level Vulnerability Repair

arXiv:2605.17444v1 Announce Type: cross Abstract: Modern software ecosystems face a rapidly growing number of disclosed vulnerabilities, increasing the need for automated repair techniques that can op

agentsarxiv-cs-ai

MiniGPT: Rebuilding GPT from First Principles

model-releasesarxiv-cs-cl

arXiv:2605.17398v1 Announce Type: new Abstract: This paper presents MiniGPT, a compact from-scratch implementation of GPT-style autoregressive language modeling in PyTorch. The aim is to rebuild the c

MixSD: Mixed Contextual Self-Distillation for Knowledge Injection

model-releasesarxiv-cs-cl

arXiv:2605.16865v1 Announce Type: new Abstract: Supervised fine-tuning (SFT) is widely used to inject new knowledge into language models, but it often degrades pretrained capabilities such as reasonin

MoCA3D: Monocular 3D Bounding Box Prediction in the Image Plane

arXiv:2603.19538v2 Announce Type: replace Abstract: Monocular 3D object understanding has largely been cast as a 2D RoI-to-3D box lifting problem. However, emerging downstream applications require ima

researcharxiv-cs-cv

Modality vs. Morphology: A Framework for Time Series Classification for Biological Signals

arXiv:2605.18483v1 Announce Type: cross Abstract: Time series classification (TSC) of biological signals has progressed from handcrafted, modality-specific approaches to deep architectures capable of

Monitoring the Internal Monologue: Probe Trajectories Reveal Reasoning Dynamics

arXiv:2605.18549v1 Announce Type: new Abstract: Large Reasoning Models (LRMs) introduce new opportunities for safety monitoring through their Chain of Thought (CoT) reasoning. However, CoT is not alwa

safetyarxiv-cs-cl

Local Ai

Mono-Hydra++: Real-Time Monocular Scene Graph Construction with Multi-Task Learning for 3D Indoor Mapping

arXiv:2605.17661v1 Announce Type: cross Abstract: Autonomous agile robots need more than metric geometry: they must understand objects, rooms, places, and spatial relations for search, inspection, exp

local-aiarxiv-cs-cv

Motion-Uncertainty-Aware Next-Best-View Planning for Moving Object Reconstruction

arXiv:2605.17593v1 Announce Type: new Abstract: Active 3D reconstruction of moving objects requires selecting informative viewpoints while accounting for object motion uncertainty during the decision-

applicationsarxiv-cs-ro

MR-SLAM: Immersive Spatial Supervision for Multi-Robot Mapping via Mixed Reality

arXiv:2605.16432v1 Announce Type: cross Abstract: Operating a multi-robot fleet for simultaneous localization and mapping (SLAM) in applications such as building inspection or warehouse-aisle monitori

applicationsarxiv-cs-ai

Multi-site PPG: An In-the-Wild Physiological Dataset from Emerging Multi-site Wearables

model-releasesarxiv-cs-lg

arXiv:2605.17859v1 Announce Type: cross Abstract: Wearables are widely used for mobile health monitoring, and photoplethysmography (PPG) is a key sensing modality for heart rate and related physiologi

Multi-task learning on partially labeled datasets via invariant/equivariant semi-supervised learning

arXiv:2605.17624v1 Announce Type: cross Abstract: We investigate the potential of invariant and equivariant semi-supervised learning for addressing the challenges of training multi-task models on part

Multilingual and Multimodal LLMs in the Wild: Building for Low-Resource Languages

arXiv:2605.17152v1 Announce Type: new Abstract: Multimodal LLMs are evolving from vision-language to tri-modality that see, hear, and read, yet pipelines and benchmarks remain English-centric and comp

safetyarxiv-cs-cl