Search: “evaluation”

Fairness Interventions in Classification: A Study on AI Explainability

arXiv:2407.14766v4 Announce Type: replace-cross Abstract: This paper presents a philosophical and experimental study of fairness interventions in AI classification, centered on the explainability and

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Applications

FedSLIM: Privacy-Preserving Federated MDL-Based Descriptive Pattern Mining Across Data Silos

DGX agent

arXiv:2607.23236v1 Announce Type: cross Abstract: Federated learning has achieved considerable success for predictive modelling, yet federated descriptive analytics remains largely unexplored. Existin

applicationsarxiv-cs-ai

28 Jul 2026

Applications

FILLER: Feature Imputation via Latent Location Exploration and Retrieval

arXiv:2607.23295v1 Announce Type: cross Abstract: In real-world machine learning applications, incomplete observations create a fundamental challenge. Researchers have come up with several ideas to ad

applicationsarxiv-cs-ai

Flash-CNNCap: Capacitance Extraction via Image Mapping

model-releasesarxiv-cs-lg

arXiv:2607.23877v1 Announce Type: new Abstract: We present Flash-CNNCap, a CNN-based capacitance extractor that reformulates full-matrix capacitance prediction as image-to-image regression over spatia

FloAff-Kitchen: Bridging Navigation and Manipulation via Canonical and Progressive Floor Affordance Learning

model-releasesarxiv-cs-ro

arXiv:2607.24207v1 Announce Type: new Abstract: Mobile manipulation requires robots to identify Floor Affordance (FloAff) that maximizes downstream manipulation success rather than merely ensuring nav

FogDrive: A Multi-Modal Synthetic Driving Dataset for Perception under Graded Fog

model-releasesarxiv-cs-cv

arXiv:2607.22698v1 Announce Type: new Abstract: Perception under adverse weather remains a critical bottleneck for reliable autonomous driving, yet existing benchmarks lack the systematic multi-modal

From peer review nuances to best practices

arXiv:2607.22681v1 Announce Type: cross Abstract: This report studies three nuances in peer review data: paper version, score version, and input format. We characterize how the variants differ, and me

researcharxiv-cs-cl

From Physics to Surrogate Intelligence: A Unified Electro-Thermo-Optimization Framework for TSV Networks

arXiv:2603.29268v2 Announce Type: replace Abstract: High-density through-substrate vias (TSVs) enable 2.5D/3D heterogeneous integration but introduce significant signal-integrity and thermal-reliabili

From RLVR to RLSVR: Task Transformation Induces Self-Verifiable Rewards for Open-Ended LLM Self-Improvement

arXiv:2607.23802v1 Announce Type: new Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) has driven recent progress in reasoning-oriented large language models (LLMs) by enabling large-sc

From Score Learning to Discretized Sampling: An End-to-End Generalization Analysis of Diffusion Models

arXiv:2607.23226v1 Announce Type: new Abstract: Despite the empirical success of score-based diffusion models, a complete theoretical understanding of how finite-sample learning, network parameterizat

From transcription to semantic corpus analysis: unsupervised learning of sentence representations for ancient languages

model-releasesarxiv-cs-cl

arXiv:2607.24542v1 Announce Type: new Abstract: Automatic Text Recognition (ATR) now supplies digital humanities with large volumes of unstructured, heterogeneous, and often noisy text in ancient lang

Generalization bounds and sample complexity for remaining useful life prediction from complete degradation trajectories

arXiv:2607.23454v1 Announce Type: new Abstract: Data-driven remaining useful life (RUL) prediction requires complete degradation trajectories for training, yet such run-to-failure data are scarce and

safetyarxiv-cs-lg

Generative Artificial Intelligence (GenAI) to convert images of queuing networks into verifiable simulation models: an open-weight LLM workflow approach

arXiv:2607.24259v1 Announce Type: new Abstract: Recent work has explored the use of Large Language Models (LLMs) to automate simulation model building, typically by generating executable code directly

Generative Augmentation for EEG Motor Imagery Classification: A Class-Conditional VAE with Cycle-Consistent Decoder Refinement

arXiv:2607.22733v1 Announce Type: new Abstract: We investigate whether a generative model can supply useful synthetic motor-imagery (MI) electroencephalography (EEG) trials that improve the accuracy o

researcharxiv-cs-cv

Agents

GNN-based Multi-Agent Control of Traffic Shockwaves in Sparse Vehicular Ad-hoc Networks

arXiv:2607.23792v1 Announce Type: cross Abstract: Traffic shockwaves are stop-and-go waves that propagate upstream through the streams of vehicles and are one of the major causes of traffic congestion

agentsarxiv-cs-lg

GOTS: Greedy Orthogonal Token Selection for High-Resolution Vision-Language Models

arXiv:2607.23913v1 Announce Type: new Abstract: Modern vision-language models (VLMs) increasingly rely on dynamic or high-resolution visual encoding, producing thousands of visual tokens that substant

GTIN: A Unified Framework for Joint Event and Time Prediction in Temporal Graphs

arXiv:2607.23556v1 Announce Type: cross Abstract: Temporal graphs are increasingly used to model dynamic systems in diverse domains such as social networks, financial networks, and traffic networks. P

Harmonized Interpretable ECG Waveform Features for Robust Cross-Dataset Clinical Prediction

model-releasesarxiv-cs-lg

arXiv:2607.23412v1 Announce Type: new Abstract: Electrocardiograms (ECGs) are widely used for cardiovascular risk prediction, yet models often fail to transfer across hospitals because of protocol, po

HeraSys: Collaborative Serving of Multiple LLM Workflows via Fine-Grained End-to-End Optimization

arXiv:2607.22578v1 Announce Type: new Abstract: The proliferation of Large Language Models (LLMs) has shifted serving systems from processing isolated requests to orchestrating high-concurrency, multi

safetyarxiv-cs-ai

Hierarchical Group-Conditional Conformal Risk Control for Selective Prediction in Language Models

arXiv:2607.24562v1 Announce Type: new Abstract: Large language models serve heterogeneous populations structured by domain, topic difficulty, and linguistic style. Conformal risk control (CRC) gives r

Hierarchical Soft Actor-Critic for Sparse-Reward Long-Horizon Reinforcement Learning

arXiv:2607.23726v1 Announce Type: cross Abstract: Exploration in sparse-reward long-horizon tasks poses significant challenges for reinforcement learning. To address these challenges, we propose a two

safetyarxiv-cs-lg

Hybrid AI-Physical Modeling for Penetration Bias Correction in X-band InSAR DEMs: A Greenland Case Study

arXiv:2504.08909v2 Announce Type: replace Abstract: Digital elevation models derived from Interferometric Synthetic Aperture Radar (InSAR) data over glacial and snow-covered regions often exhibit syst

safetyarxiv-cs-ai

Hardware

Hybrid Semantic and Spectral Ensemble for Robust Synthetic Image Source Attribution

arXiv:2607.22808v1 Announce Type: cross Abstract: The rapid advancement of text-to-image (T2I) models has necessitated robust Synthetic Image Source Attribution (SIA) methodologies. A critical challen

hardwarearxiv-cs-ai

IB-Flow: Information Bottleneck-Guided CFG Distillation for Few-Step Text-to-Image Generation

arXiv:2607.09133v2 Announce Type: replace-cross Abstract: While large-scale text-to-image generative models have achieved unprecedented visual performance, their inherent reliance on multi-step iterat

IJCB-AFMFR 2026: Competition on Adapting Foundation Models for Face Recognition Using Synthetic Training Data

arXiv:2607.24422v1 Announce Type: new Abstract: This paper presents a summary of the Competition on Adapting Foundation Models for Face Recognition Using Synthetic Training Data (AFMFR), held at the 2

safetyarxiv-cs-cv

IKS-Instruct: A 24,000-Example Multilingual Dataset for Teaching Language Models Indian Knowledge Systems

model-releasesarxiv-cs-cl

arXiv:2607.23322v1 Announce Type: new Abstract: Instruction tuning has become the standard method for adapting large language models to follow human intent, yet existing instruction datasets are domin

Imprompt: A Language Framework for Prompt Programming

arXiv:2607.22683v1 Announce Type: new Abstract: With the unprecedented success of Language Models (LMs), the science of Prompt Engineering has evolved the powerful idea of Prompt Programming, where pr

In-Context Learning as Implicit Policy Gradient

arXiv:2607.23153v1 Announce Type: cross Abstract: Recent work has shown that large language models (LLMs) can iteratively improve their outputs by incorporating generated samples and their correspondi

safetyarxiv-cs-ai

Indic DiarBench: A Multilingual Joint Diarization and ASR Benchmark for Indian Languages

arXiv:2607.23808v1 Announce Type: cross Abstract: In this work, we introduce Indic DiarBench, a speaker diarization and ASR benchmark dataset spanning all 22 scheduled languages of India. This corpus

Infinite-Precision Autoregressive Modeling for Vector Graphics and Layouts

arXiv:2601.05680v2 Announce Type: replace-cross Abstract: While Transformer-based autoregressive models excel in data generation, their token discretization strategy inherently limits their precision

Tutorials

Invariant Discovery for Networked Systems

arXiv:2607.22944v1 Announce Type: cross Abstract: Invariants, the relations expected to hold among measured signals of a network, underpin applications from verification to traffic generation, telemet

tutorialsarxiv-cs-ai

Agents

JarvisHub: An Open Harness for Canvas-Native Multimodal Creative Agents

arXiv:2607.23588v1 Announce Type: new Abstract: Creative AI is moving from single-step asset generation toward long-horizon multimodal production. Although recent generative models can synthesize high

agentsarxiv-cs-cv

Hardware

Kalypso: Relational LLM Serving

arXiv:2607.23815v1 Announce Type: cross Abstract: Large language models are increasingly used as semantic operators for filtering, extracting, ranking, joining, and transforming unstructured data. Exi

hardwarearxiv-cs-ai

Keep It InMind: Benchmarking the Implicit-Association Blind Spot in Agent Memory

model-releasesarxiv-cs-cl

arXiv:2607.24368v1 Announce Type: new Abstract: Long-term memory systems store what a user says in an external store and retrieve it when a related query arrives. This interface rests on an assumption

Tutorials

Kernel-SDF: An Open-Source Library for Real-Time Signed Distance Function Estimation using Kernel Regression

arXiv:2603.29227v2 Announce Type: replace Abstract: Accurate and efficient scene representation is crucial for robotic tasks such as motion planning, manipulation, and navigation. Signed distance func

tutorialsarxiv-cs-ro

Agents

Knowledge-Centric Agents for Workflow Generation in ComfyUI

arXiv:2607.15845v2 Announce Type: replace Abstract: Workflow generation in visual creation systems such as ComfyUI demands not only syntactic accuracy but also expert-level reasoning over modular comp

agentsarxiv-cs-ai

LanteRn: Latent Visual Structured Reasoning

arXiv:2603.25629v2 Announce Type: replace Abstract: While language reasoning models excel in many tasks, visual reasoning remains challenging for current large multimodal models (LMMs). As a result, m

researcharxiv-cs-cv

LC-SEPLM: long-range contact-supervised adaptation for sequence-only protein representation learning

arXiv:2607.22777v1 Announce Type: cross Abstract: Protein language models learn transferable sequence representations. However, because they primarily model contextual dependencies along amino-acid se

LEACL: LLM-Enhanced Automatic Curriculum Learning for Reinforcement Learning in Long-Horizon Manipulation Tasks

model-releasesarxiv-cs-ro

arXiv:2607.23515v1 Announce Type: new Abstract: Long-horizon manipulation tasks pose significant challenges for reinforcement learning due to sparse reward signals and long horizons. Automatic curricu

Learning from the Descent Direction: Adaptive Gradient Descent under One-Sided Holder Regularity

arXiv:2607.22906v1 Announce Type: new Abstract: We study adaptive gradient descent for continuously differentiable, possibly nonconvex objectives under one-sided Holder regularity. Unlike classical Ho

Learning Reusable Hybrid Motion Priors for Humanoid Locomotion from Motion Imitation

arXiv:2607.24083v1 Announce Type: new Abstract: Reinforcement learning can produce robust humanoid controllers, but each new task is typically trained as a separate policy with its own reward design a

safetyarxiv-cs-lg

Learning Sampling Parameters for Diffusion Models

model-releasesarxiv-cs-cv

arXiv:2607.23488v1 Announce Type: cross Abstract: Text-to-image diffusion models expose many inference-time sampling parameters, including prompts, negative prompts, classifier-free guidance scales, a

Learning to Access Computation: Accessibility Plasticity as a Principle of Adaptive Intelligence

arXiv:2607.22748v1 Announce Type: cross Abstract: Modern neural networks primarily adapt through parameter modification within predefined computational structures. While recent methods introduce modul

Local Ai

Let AI Agents Translate Networks, Not Reason About Them

arXiv:2607.22947v1 Announce Type: new Abstract: A formal model enables verifying reachability, localizing an outage, or anticipating the blast radius of a change. Yet, virtually no production network

local-aiarxiv-cs-ai

LLM-based Source Code Compression via Thresholded Symbol Ranking

arXiv:2607.24192v1 Announce Type: cross Abstract: We study the problem of lossless compression of source code, motivated by the storage demands of large-scale software archives, such as Software Herit

researcharxiv-cs-cl

Long-Tailed Medical Image Classification

arXiv:2607.23883v1 Announce Type: new Abstract: In this paper, we examine the difficulties of using standard techniques for medical image classification due to long-tailed distributions (wherein rarer

safetyarxiv-cs-cv

Machine Learning for Cloud Detection in IASI Measurements: A Data-Driven SVM Approach with Physical Constraints

arXiv:2508.10120v2 Announce Type: replace-cross Abstract: Cloud detection is fundamental for the interpretation and operational exploitation of hyperspectral infrared sounders, yet the capability of i

Markerless Motion Capture in Routine Clinical Upper Limb Assessments: Validity and Insights Beyond Ordinal Scoring

arXiv:2607.23608v1 Announce Type: new Abstract: The Action Research Arm Test (ARAT) is a widely-used upper limb outcome measure in neurorehabilitation, but its ordinal scoring is subjective and suffer

researcharxiv-cs-cv