Search: “evaluation”

RolloutPipe: Overlapping Pipelined Rollout and Training in Disaggregated On-Policy LLM Reinforcement Learning

arXiv:2606.26997v1 Announce Type: cross Abstract: Large language model (LLM) post-training for reasoning increasingly relies on reinforcement learning with verifiable rewards (RLVR), where models lear

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Model Releases

RoPEMover: Depth-Aware Object Relocation via Positional Embeddings

DGX agent

arXiv:2606.27332v1 Announce Type: new Abstract: Moving an object in a single image requires geometry-consistent spatial rearrangement, including handling occlusions, revealing previously unseen region

model-releasesarxiv-cs-cv

26 Jun 2026

Sample-efficient Transfer Reinforcement Learning via Adaptive Reward Shaping and Policy-Ratio Reweighting Strategy

arXiv:2606.26527v1 Announce Type: new Abstract: Transfer learning improves policy learning efficiency by reusing knowledge from source tasks, providing a feasible paradigm for safe and efficient auton

Tutorials

SatSplatDiff: Geometry-preserving generative refinement for high-fidelity satellite Gaussian Splatting

arXiv:2606.27223v1 Announce Type: new Abstract: Gaussian Splatting has been recently explored for satellite 3D reconstruction, demonstrating flexibility and efficiency in representing radiometrically

tutorialsarxiv-cs-cv

Local Ai

Scaling Nonlinear Optimization: Many Problems One GPU

arXiv:2606.26341v1 Announce Type: new Abstract: Many robotics problems, including trajectory optimization, inverse kinematics, and contact-rich motion planning, reduce to nonlinear programs (NLPs). Ma

local-aiarxiv-cs-ro

SciFig: Towards Automating Editable Figure Generation for Scientific Papers

arXiv:2601.04390v2 Announce Type: replace Abstract: High-quality methodology figures are central to scientific communication, yet they remain difficult and time-consuming to create. Such figures must

See & Sniff: Learning Visuo-Olfactory Representations

model-releasesarxiv-cs-cv

arXiv:2606.27307v1 Announce Type: new Abstract: While modern multimodal models integrate vision with language, audio, or touch, olfaction remains largely unexplored due to the lack of paired visuo-olf

ShareLock: A Stealthy Multi-Tool Threshold Poisoning Attack Against MCP

arXiv:2606.27027v1 Announce Type: cross Abstract: With the rapid evolution of LLM-driven agents, Model Context Protocol (MCP), an open protocol bridging LLMs with external tools, has quickly become fo

SharQ: Bridging Activation Sparsity and FP4 Quantization for LLM Inference

arXiv:2606.26587v1 Announce Type: cross Abstract: Low-bit floating-point formats and semi-structured sparsity are increasingly supported by modern accelerators, yet combining them for LLM activation c

Applications

SignSparK: Efficient Multilingual Sign Language Production via Sparse Keyframe Learning

arXiv:2603.10446v4 Announce Type: replace Abstract: Sign Language Production (SLP) faces a fundamental trade-off: direct text-to-pose models suffer from regression-to-the-mean effects, while dictionar

applicationsarxiv-cs-cv

Simulation-based inference for rapid Bayesian parameter estimation in epidemiological models: a comparison with MCMC

arXiv:2606.27286v1 Announce Type: new Abstract: Mechanistic epidemiological models are widely used to support infectious disease forecasting and public-health decision making. Bayesian calibration of

Socratic agents for autonomous scientific discovery in high-dimensional physical systems

arXiv:2606.26722v1 Announce Type: new Abstract: The automation of scientific discovery has reached an inflection point. While AI systems now operate instruments, optimize parameters and generate hypot

agentsarxiv-cs-ai

SOLAR: AI-Powered Speed-of-Light Performance Analysis

arXiv:2606.26383v1 Announce Type: cross Abstract: How fast could a deep-learning model run on target hardware, and how far is today's implementation from that limit? These questions are central to sof

SPARK: Low Latency Single-Camera 3D Pose Estimation for Autonomous Racing using Keypoints

arXiv:2606.17936v2 Announce Type: replace Abstract: In autonomous racing, fast detection of other participants' movements is required to plan safe, collision-free trajectories with non-cooperative opp

agentsarxiv-cs-ro

SpatialFlow-GRPO: Where Spatial Credit Drives Image Editing

arXiv:2606.26872v1 Announce Type: new Abstract: Recent online reinforcement learning has substantially improved image editing quality. However, existing Flow-GRPO-style methods usually rely on a singl

safetyarxiv-cs-cv

SSM Adapters via Hankel Reduced-order Modeling: Injection Site Determines Task Suitability in Long-Context Fine-Tuning

arXiv:2606.26290v1 Announce Type: cross Abstract: While parameter-efficient fine-tuning (PEFT) typically targets attention projectors, its efficacy for tasks requiring sequential state accumulation re

State Representation Matters in Deep Reinforcement Learning: Application to Energy Trading

arXiv:2606.27032v1 Announce Type: cross Abstract: Energy trading decisions depend not only on current market prices, but also on expected future market conditions, and operational constraints. This ma

safetyarxiv-cs-ai

State-Specific Respiratory Signatures for Affective and Stress Recognition: Interpretable Respiratory Markers, Autocorrelation Lags, and Compact CNN Models

arXiv:2606.26723v1 Announce Type: cross Abstract: Respiratory activity is a direct and interpretable physiological channel for wearable stress and affective-state recognition, yet many studies emphasi

TAVR-VLM: Risk-Conditioned Causal Grounding for Hallucination-Resistant Report Generation

arXiv:2606.26874v1 Announce Type: new Abstract: Transcatheter Aortic Valve Replacement (TAVR) planning requires meticulous multimodal reasoning. However, adapting Multimodal Large Language Models (MLL

Local Ai

Temporal Validity in Retrieval Memory: Eliminating Stale-Fact Errors for AI Agents over Evolving Knowledge

arXiv:2606.26511v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG) gives agents access to accumulated knowledge, but has no model of time. When a fact changes (e.g., a function is

local-aiarxiv-cs-ai

TF-TI2I: Training-Free Text-and-Image-to-Image Generation via Multi-Modal Implicit-Context Learning in Text-to-Image Models

model-releasesarxiv-cs-cv

arXiv:2503.15283v2 Announce Type: replace Abstract: Text-and-Image-To-Image (TI2I), an extension of Text-To-Image (T2I), integrates image inputs with textual instructions to enhance image generation.

The Role of Input Dimensionality in the Emergence and Targeted Control of Adversarial Examples

arXiv:2606.26207v1 Announce Type: cross Abstract: Several theoretical works have tried to explain the adversarial vulnerability of deep neural networks through properties of high-dimensional geometry.

Thinking Like a Scientist? A Structural Study of LLM-Generated Research Methods

arXiv:2606.26130v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly used to guide research methodology, yet their default methodological tendencies under minimal prompting

Topology-Informed Neural Networks for Flood Detection in Optical and Synthetic Aperture Radar Imagery

arXiv:2606.26204v1 Announce Type: new Abstract: Floods frequently impact regions around the world. Rapid and accurate flood detection is crucial for emergency response and timely mitigation of human a

Towards Explainable Adjudicative Variance: Quantifying Judicial Discretion via Gated Multi-Task Learning

model-releasesarxiv-cs-cl

arXiv:2606.27069v1 Announce Type: new Abstract: Legal outcome prediction must disentangle objective case facts from adjudicative context. Merit-based rulings rely on factual evidence while technical d

Trust in Generative AI for Health Information Consumption and the Effect of Learned Dependency: An Experimental Investigation

arXiv:2606.20605v2 Announce Type: replace-cross Abstract: Background: Generative artificial intelligence (GenAI) is increasingly used for health information, yet its influence on users' trust calibrat

Unbiased Canonical Set-Valued Oracles Via Lattice Theory

arXiv:2606.26418v1 Announce Type: new Abstract: A non-agentic 'oracle' AI that estimates probabilities of future events faces a self-reference problem: once its answer is learned and acted upon, it ca

agentsarxiv-cs-ai

Applications

Uncertainty-Aware Ankle Exoskeleton Control

arXiv:2508.21221v2 Announce Type: replace Abstract: Lower limb exoskeletons show promise to assist human movement, but their utility is limited by controllers designed for discrete, predefined actions

applicationsarxiv-cs-ro

Uncertainty quantification via conformal prediction in data assimilation

arXiv:2606.27001v1 Announce Type: new Abstract: Quantifying the evolution of uncertainty is critical to both probabilistic forecasting and data assimilation in numerical weather prediction. In this st

Understanding Domain-Aware Distribution Alignment in Budgeted Entity Matching

arXiv:2606.27342v1 Announce Type: cross Abstract: Entity Matching (EM) is a core operation in the data integration pipeline, where records from different sources are compared to determine whether they

safetyarxiv-cs-ai

UniFlow: Zero-Shot LiDAR Scene Flow for Autonomous Vehicles

arXiv:2511.18254v3 Announce Type: replace Abstract: LiDAR scene flow is the task of estimating per-point 3D motion between consecutive point clouds. Recent methods achieve centimeter-level accuracy on

agentsarxiv-cs-cv

Unsupervised Memory-Enhanced Video Transformers: Obstacle Detection for Autonomous Agricultural Rover

arXiv:2606.26151v1 Announce Type: cross Abstract: While autonomous rovers have become indispensable to precision farming, achieving consistent operational safety remains a critical challenge. Conventi

safetyarxiv-cs-ai

Use What You Know: Causal Foundation Models with Partial Graphs

arXiv:2602.14972v2 Announce Type: replace Abstract: Estimating causal quantities traditionally relies on bespoke estimators tailored to specific assumptions. Recently proposed Causal Foundation Models

Utilizing Cognitive Signals Generated during Human Reading to Enhance Keyphrase Extraction from Microblogs

arXiv:2606.26485v1 Announce Type: new Abstract: Microblogging platforms generate massive amounts of short, noisy, and dispersed user content, making automatic keyphrase extraction (AKE) an important b

What Survives When You Compress a Recursive Reasoner for the Edge?

arXiv:2606.26488v1 Announce Type: new Abstract: Recursive reasoning models can solve complex structured tasks with only a few million parameters by repeatedly updating a latent state. Deploying these

When to Write and When to Suppress: Route-Specialized Dual Adapters for Memory-Assisted Knowledge Editing

model-releasesarxiv-cs-lg

arXiv:2606.14668v3 Announce Type: replace Abstract: Knowledge editing systems must update selected facts while preserving nearby but irrelevant behavior. This paper studies this problem in a memory-as

Where Larger Models Excel: The Primacy of Constraint-Guided Reasoning

arXiv:2606.26108v1 Announce Type: new Abstract: Larger language models consistently outperform smaller ones on reasoning benchmarks, yet the reasoning differences underlying this gap remain underexplo

XMSE-Aware Adaptive Empirical Bayes Estimation

arXiv:2606.26975v1 Announce Type: cross Abstract: Empirical Bayes (EB) estimators can match the first-order asymptotic risk of maximum likelihood (ML) while behaving very differently at second order:

A 3D-Printable Dataset for Fair Testing and Comparisons of Tactile Sensors

model-releasesarxiv-cs-lg

arXiv:2606.25886v1 Announce Type: cross Abstract: Existing texture datasets for tactile sensing primarily consist of sensor readings from a specific sensor interacting with available surfaces/objects

A cross-process welding penetration status prediction algorithm based on unsupervised domain adaptation in laser and TIG welding

arXiv:2606.26078v1 Announce Type: new Abstract: Supervised deep learning has been widely used for weld penetration state classification; however, its performance often degrades significantly under dom

researcharxiv-cs-cv

A Flow-rate-conserving CNN-based Domain Decomposition Method for Blood Flow Simulations

model-releasesarxiv-cs-lg

arXiv:2509.15900v2 Announce Type: replace-cross Abstract: This work aims to predict blood flow with non-Newtonian viscosity in stenosed arteries using convolutional neural network (CNN) surrogate mode

A Geometry-Aware Efficient Algorithm for Compositional Entropic Risk Minimization

arXiv:2602.02877v2 Announce Type: replace Abstract: This paper studies optimization for a family of problems termed extbf{compositional entropic risk minimization}, in which each data's loss is formul

A Neuromorphic Trigger for Efficient Audio Event Detection

arXiv:2606.17775v2 Announce Type: replace-cross Abstract: Efficient processing of continuous audio streams remains a key challenge for real-time and resource-constrained systems. This paper introduces

A Spectral Phase Diagram for Binary Few-Shot Classification: Intrinsic Dimensionality, Geometric Saturation, and Representational Diagnosis

arXiv:2606.24903v1 Announce Type: new Abstract: Deciding when to stop collecting labeled examples is a fundamental but undertheorized problem in applied machine learning. The saturation index S(K) = o

A Systematic Analysis of Hybrid Linear Attention

arXiv:2507.06457v2 Announce Type: replace Abstract: Transformers face quadratic complexity and memory issues with long sequences, prompting the adoption of linear attention mechanisms using fixed-size

ACT-JEPA: Novel Joint-Embedding Predictive Architecture for Efficient Policy Representation Learning

arXiv:2501.14622v5 Announce Type: replace Abstract: Learning efficient representations for decision-making policies is a challenge in imitation learning (IL). Current IL methods require expert demonst

Adapting Self-Supervised Speech Representations for Cross-lingual Dysarthria Detection in Parkinson's Disease

arXiv:2603.22225v3 Announce Type: replace Abstract: The limited availability of dysarthric speech data makes cross-lingual detection an important but challenging problem. A key difficulty is that spee

Adaptive Joint Compression and Synchronisation in Federated Split Learning for IoT Rainfall Prediction

arXiv:2606.25003v1 Announce Type: new Abstract: Federated split learning (FSL) enables collaborative training across bandwidth-constrained IoT devices, but repeated activation and gradient exchange cr