Search: “evaluation”

Loop-Mamba: A Loop Mamba with Degradation-Aware and Shared Memory for Old Photo Restoration

arXiv:2608.02346v1 Announce Type: new Abstract: Old photographs often suffer from multiple coupled degradations, including scratches, cracks, fading, blur, noise, and missing regions, severely degradi

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Model Releases

MAPLE: Metadata Augmented Private Language Evolution

DGX agent

arXiv:2603.19258v2 Announce Type: replace Abstract: Differentially private (DP) fine-tuning of large language models (LLMs) requires massive compute and full model access, which rules out state-of-the

model-releasesarxiv-cs-cl

4 Aug 2026

MDTD-ArtIR: Benchmarking Image Editing and Restoration Models for Art Image Restoration under Texture-Overlay Degradations

arXiv:2608.00736v1 Announce Type: new Abstract: Restoring severely degraded visual media still remains a formidable challenge, as existing methods often hallucinate unnatural textures and contents, st

MedSAM2-Anatomy: Training-Free Inference-Time Optimization for Musculoskeletal Segmentation

arXiv:2608.00195v1 Announce Type: cross Abstract: High-resolution 3D segmentation of hip and shoulder anatomy from CT and MRI is essential for surgical planning, yet frozen segmentation models often f

Minute-Scale Training for Microrobot Navigation

model-releasesarxiv-cs-ro

arXiv:2608.00854v1 Announce Type: new Abstract: Microrobots hold significant potential for various applications, where targeted navigation is a basic requirement. Deep reinforcement learning (DRL) has

Tutorials

Modeling Unknown Nonlocal PDE Systems via Flow Map Learning

arXiv:2608.00400v1 Announce Type: new Abstract: Nonlocal partial differential equations arise in many applications but are often difficult to model and learn because of the presence of nonlocal operat

tutorialsarxiv-cs-lg

MoRAL: Sensor-Grounded BEV Reasoning for Compact VLMs toward Edge-Oriented Autonomous Driving

arXiv:2608.02449v1 Announce Type: new Abstract: Deploying vision-language models (VLMs) for safety-critical spatial reasoning on resource-constrained autonomous driving platforms requires both compact

Morphology Aware Reversible Semantic Tokenization and Hierarchical Word Composition for Tamil Language Models

model-releasesarxiv-cs-cl

arXiv:2608.01153v1 Announce Type: new Abstract: Statistical subword tokenizers can process arbitrary text, but their units need not align with lexical or grammatical structure. This is especially impo

Motion Beyond Morphology: Bootstrapping Cross-Category Motion Transfer from Abstract Motion Representations

arXiv:2608.01628v1 Announce Type: new Abstract: Video motion transfer aims to animate a target object using dynamics from a reference video. Existing formulations largely rely on fixed structural corr

researcharxiv-cs-cv

Multi-Source Dynamic Graph Learning for Compound-Flood Forecasting in Managed Coastal Systems

arXiv:2608.01775v1 Announce Type: new Abstract: Compound flooding in managed coastal systems is influenced by hydrological conditions and water-management activity observed across multiple monitoring

safetyarxiv-cs-lg

Native Multilingual Chain-of-Thought Reasoning in Low-Resource Southeast Asian Languages

arXiv:2608.00533v1 Announce Type: new Abstract: Large Language Models have achieved substantial progress in reasoning capabilities. Yet in low-resource native settings, many suffer from cross-lingual

safetyarxiv-cs-cl

Neural Circuit Function Inference with LLMs

arXiv:2608.00059v1 Announce Type: new Abstract: The success of connectome mapping now shifts the challenge of understanding the nervous system to the interpretation of neural circuits. Here, we devise

Neural Surrogate HMC: On Using Neural Likelihoods for Hamiltonian Monte Carlo in Simulation-Based Inference

arXiv:2407.20432v3 Announce Type: replace Abstract: Bayesian inference methods such as Markov Chain Monte Carlo (MCMC) typically require repeated computations of the likelihood function, but in some s

NISF++: Geometrically-grounded implicit representations of 3D+time cardiac function from 2D short- and long-axis MR views

arXiv:2608.00752v1 Announce Type: new Abstract: Clinical acquisition in cardiac magnetic resonance (CMR) imaging involves obtaining cross-sectional planes of the heart along the radial and longitudina

Nonlinear Laplacians Improve Signed-Directed Graph Learning

arXiv:2608.00836v1 Announce Type: new Abstract: While signed-directed graphs have been studied using linear Laplacians in the design of graph neural networks, relatively little research has focused on

Nonparametric Distribution Regression Re-calibration

arXiv:2602.13362v2 Announce Type: replace-cross Abstract: A key challenge in probabilistic regression is ensuring that predictive distributions accurately reflect true empirical uncertainty. Minimizin

safetyarxiv-cs-lg

Nova: An End-to-End MLIR Compiler for Deep Learning

model-releasesarxiv-cs-lg

arXiv:2608.00029v1 Announce Type: cross Abstract: The performance of deep learning models at scale relies heavily on how effectively high-level mathematical operations are mapped to underlying physica

Observatorio Lazaro: A self-populating database of anglicism usage in the Spanish press

arXiv:2608.00713v1 Announce Type: new Abstract: This paper describes Observatorio Lazaro, a language resource that monitors unassimilated lexical borrowings (predominantly English lexical borrowings o

On the Limits of Machine-Learned Ranking for Modern Microarchitectural Policies

arXiv:2608.01041v1 Announce Type: cross Abstract: Machine-learning predictors estimate processor performance far faster than cycle-level simulation. For design-space exploration, however, the valuable

On the Limits of Support-Preserving Alignment and Bounded Filtering

arXiv:2607.18295v2 Announce Type: replace Abstract: We study whether alignment schemes that reshape a base model's output distribution, combined with bounded safety filters, can drive the probability

safetyarxiv-cs-lg

On the Viability of Semi-Supervised Segmentation Methods for Statistical Shape Modeling

arXiv:2407.15260v3 Announce Type: replace Abstract: Statistical Shape Models (SSMs) excel at identifying population level anatomical variations, which is at the core of various clinical and biomedical

Onboard Satellite Image Classification for Earth Observation: A Comparative Study of ViT Models

arXiv:2409.03901v4 Announce Type: replace Abstract: Remote sensing (RS) image classification is central to Earth observation, but onboard deployment requires models that are accurate, efficient, and r

researcharxiv-cs-cv

One Query, Many Scales: Sparse Mixture-of-Experts for Efficient Hierarchical Cross-View Geo-Localization

arXiv:2608.01060v1 Announce Type: new Abstract: Cross-view geo-localization (CVGL) retrieves geo-tagged satellite imagery for a ground-view query. Most systems exhaustively search a flat, fixed-resolu

OpenDebateEvidence: A Massive-Scale Argument Mining and Summarization Dataset

arXiv:2406.14657v4 Announce Type: replace Abstract: We introduce OpenDebateEvidence, a comprehensive dataset for argument mining and summarization sourced from the American Competitive Debate communit

Applications

Optical Flow from Photons

arXiv:2608.00499v1 Announce Type: new Abstract: Optical flow remains challenging in high-speed and low-light scenes, where the limited frame rate and sensitivity of conventional cameras lead to motion

applicationsarxiv-cs-cv

OSMDA: OpenStreetMap-based Domain Adaptation for Remote Sensing VLMs

arXiv:2603.11804v3 Announce Type: replace Abstract: Vision-Language Models (VLMs) adapted to remote sensing rely heavily on domain-specific image-text supervision, yet high-quality annotations for sat

PALMs: Using Multi Construct-Grounded Rationales for Modeling Population Preferences in LLMs

arXiv:2608.01458v1 Announce Type: new Abstract: Large language models are being extensively used to simulate individual user behavior, yet faithfully representing a population requires capturing the s

safetyarxiv-cs-cl

Agents

PB^2: Preference Space Exploration via Population-Based Methods in Preference-Based Reinforcement Learning

arXiv:2506.13741v2 Announce Type: replace-cross Abstract: Preference-based reinforcement learning (PbRL) has emerged as a promising approach for learning behaviors from human feedback without predefin

agentsarxiv-cs-lg

Physical Self-Supervised Learning: IMU Sensing without Manual Labels

arXiv:2607.18361v2 Announce Type: replace Abstract: Deep neural networks have become a promising approach for IMU-based sensing, but their scalability is fundamentally limited by costly labeled data a

Picking the right agent harness is now a crucial skill for any AI engineer. Imagine using the same model, same task, and same prompt. Now mo…

Picking the right agent harness is now a crucial skill for any AI engineer. Imagine using the same model, same task, and same prompt. Now move it between two agent harnesses and the cost per success c

model-releasesdair-ai--x

PlantRig - From Bones to Branches: Adaptation of Autoregressive Rigging Models for Plant Skeletal Reconstruction

arXiv:2608.01072v1 Announce Type: new Abstract: Autoregressive rigging models such as UniRig and SkinTokens perform well on articulated characters, but their ability to generalize to plant structures

Predicting Startup Exit from Textual Descriptors - A Computational Linguistics Framework

arXiv:2608.00045v1 Announce Type: new Abstract: This study shows that textual descriptors alone can predict early-stage startup success, defined as Exit, without relying on contextual, financial, or h

Agents

PRISM: Privileged Probabilistic Latent Supervision for End-to-End Autonomous Driving Motion Planning

arXiv:2608.01201v1 Announce Type: cross Abstract: End-to-end autonomous driving (E2E AD) systems integrate perception, prediction, and planning into a single differentiable architecture. While these m

agentsarxiv-cs-cv

Probabilistic Reachable-Action Verification of Visuomotor Policies via Set-Based Training

arXiv:2608.02545v1 Announce Type: new Abstract: Reachability analysis for visuomotor policies is difficult because large visual encoders make end-to-end set propagation computationally expensive and e

safetyarxiv-cs-ro

ProtoAct: Turning Wet-Lab Protocols into Embodied Robotic Actions

arXiv:2608.01690v1 Announce Type: new Abstract: Biological wet-lab protocols are written for trained researchers and often leave routine operations, state-dependent conditions, and contextual paramete

researcharxiv-cs-ro

Protocol generalisation for brain tissue microstructure estimation via hypernetwork-controlled geometric deep learning

arXiv:2608.02053v1 Announce Type: cross Abstract: Brain tissue microstructure estimation with machine learning provides higher computational efficiency than conventional fitting. However, machine lear

QR-Erase: Efficient Subspace-Based Machine Unlearning with Layer Localization

arXiv:2608.01422v1 Announce Type: new Abstract: Machine unlearning seeks to remove targeted information from trained models without requiring costly retraining. Existing optimization-based methods oft

QuASH: Using Natural-Language Heuristics to Query Visual-Language Robotic Maps

arXiv:2510.14546v2 Announce Type: replace Abstract: Embeddings from Visual-Language Models are increasingly utilized to represent semantics in robotic maps, offering an open-vocabulary scene understan

researcharxiv-cs-ro

Question Begets Question: Self-Evolving Curriculum for Reinforcement Fine-Tuning on Competition Mathematics

arXiv:2608.01522v1 Announce Type: cross Abstract: Teaching a language model a skill it has not mastered is obstructed by three recurring difficulties: training data is scarce, ground-truth reasoning t

Quick on the Uptake: Eliciting Implicit Intents from Human Demonstrations for Personalized Mobile-Use Agents

arXiv:2508.08645v3 Announce Type: replace Abstract: As multimodal large language models advance rapidly, the automation of mobile tasks has become increasingly feasible through the use of mobile-use a

safetyarxiv-cs-cl

QWRF-Net: A Quantum-Wavelet Framework with Rectified Flow for Short-Term Precipitation Nowcasting

arXiv:2608.01626v1 Announce Type: new Abstract: Short-term precipitation nowcasting is important for hydrometeorological early warning, especially when intense convective rainfall may trigger urban fl

Applications

RAG Strategies for Natural Language-Based SQL Query and REST API Call Generation

arXiv:2602.07086v2 Announce Type: replace-cross Abstract: Enterprise software systems commonly expose business functionality through both relational databases and REST APIs. Accessing these interfaces

applicationsarxiv-cs-cl

Ranking Image Fusion the Way Humans Do: A Learned Pairwise Preference Metric for Infrared-Visible Fusion Assessment

arXiv:2608.01301v1 Announce Type: new Abstract: Infrared-visible image fusion (IVIF) has no ideal fused reference, so fusion algorithms are routinely ranked by scalar objective metrics that formalize

RAP: KV-Cache Compression via RoPE-Aligned Pruning

model-releasesarxiv-cs-lg

arXiv:2602.02599v4 Announce Type: replace Abstract: Long-context inference in large language models (LLMs) is bottlenecked by the memory and compute of the key-value (KV) cache. Structured pruning is

Real-Time Visual Obstruction Detection in Surgical Augmented Reality

arXiv:2608.00232v1 Announce Type: new Abstract: Surgical augmented reality (AR) can provide contextual guidance by overlaying virtual annotations, tool cues, and procedural information onto the surgic

ReasonCast: Towards Explainable Time Series Forecasting with Reasoning

model-releasesarxiv-cs-lg

arXiv:2608.01875v1 Announce Type: cross Abstract: Most time series (TS) models are specialized for a single task, either understanding (i.e., returning text answers about a TS) or generation (i.e., re

Applications

ReMiX-MAE: Learning Missing-Channel Cross-Modal Representations from RGB-Only Clinical Facial Videos for Sympathetic-Mediated Pain Assessment

arXiv:2608.02561v1 Announce Type: new Abstract: Automated pain assessment in real clinics is limited by scarce clinically grounded facial video data with weak labels (often sequence-level self-report)

applicationsarxiv-cs-cv

Representation Transfer of Foundation Models for Ultra-Widefield Retinal Imaging

arXiv:2608.00586v1 Announce Type: new Abstract: Despite the widespread adoption of foundation models as feature extractors for medical imaging, relatively little is understood about how different pret

researcharxiv-cs-cv