Search: “models”

CheMLFlow: An Open-Source Platform for Cheminformatics and Materials Informatics Applications

arXiv:2608.04942v1 Announce Type: cross Abstract: CheMLFlow is an open-source platform for building and executing end-to-end, high-throughput, and agentic workflows for scientific and technological ap

agentsarxiv-cs-ai

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Research

Consistency-Driven Co-Evolution for Self-Supervised Cross-Representation Learning

DGX agent

arXiv:2608.04926v1 Announce Type: cross Abstract: As chart images, tabular data, and visualization code play increasingly important roles across diverse domains, cross-representation understanding acr

researcharxiv-cs-ai

6 Aug 2026

Feedback Loops and Code Perturbations in LLM-based Software Engineering: A Case Study on a C-to-Rust Translation System

arXiv:2512.02567v2 Announce Type: replace-cross Abstract: The advent of strong generative AI has a considerable impact on various software engineering tasks such as code repair, test generation, or la

FM4WiFi: Flow Matching for Multi-AP Coordination in Dense Deployments of Beyond Wi-Fi 8 Networks

arXiv:2608.04050v1 Announce Type: cross Abstract: Wi-Fi networks are moving beyond random channel access toward tightly coordinated operation across access points (APs), a shift reflected in Wi-Fi 8's

researcharxiv-cs-lg

Free-Lunch Augmentation by Revisiting Diffusion-Based Data Generation for Cross-Domain Few-Shot Object Detection

arXiv:2608.04394v1 Announce Type: new Abstract: Cross-Domain Few-Shot Object Detection (CDFSOD) aims to transfer knowledge from data-rich upstream generic domains to downstream expert domains using sc

From Understanding to Erasing: Towards Complete and Stable Video Object Removal

arXiv:2604.01693v2 Announce Type: replace Abstract: Video object removal aims to erase target objects while reconstructing visually plausible and temporally coherent content. However, target objects o

local-aiarxiv-cs-cv

Guideline-as-Oracle: Zero-Annotation Training of an Ophthalmic Telephone Triage Agent

arXiv:2608.04772v1 Announce Type: cross Abstract: Scaling supervision for multi-turn medical agents is difficult because expert dialogue annotation is costly and clinical conversations are privacy-res

Human-in-the-Loop Atlas-Based 3D Asset Segmentation for Interactive Content Workflows

arXiv:2606.17824v2 Announce Type: replace-cross Abstract: Segmenting 3D assets into meaningful regions remains challenging, especially when segmentation criteria are application-dependent and require

applicationsarxiv-cs-ai

InvFlowFD: Reference-Free and Background-Set-Free Perceptual Music Quality Metric with Flow Matching Inversion

arXiv:2608.04142v1 Announce Type: cross Abstract: Existing reference-free methods for evaluating music perceptual quality alleviate the need for paired noisy-clean data, but they still rely on a backg

IRIS: A Visual Cortex-Inspired Framework for Analyzing Orientation Selectivity in Vision Transformers

arXiv:2608.05122v1 Announce Type: new Abstract: Vision transformers (ViTs) have become the de facto standard for image encoding across many perception tasks. Despite their empirical success, it remain

local-aiarxiv-cs-cv

Learning Sexism Detection Using Multi-Agent Perspectivist Preference Optimization

arXiv:2608.04056v1 Announce Type: new Abstract: When people label text for sexism, they often disagree, and not because some of them are wrong: they genuinely perceive sexism differently. Most NLP sys

agentsarxiv-cs-cl

Link prediction on multi-relational graphs from an influence propagation perspective

arXiv:2608.05016v1 Announce Type: cross Abstract: Predicting the existence and type of links (edges) between nodes in a multi-relational graph is key for applications from social interaction predictio

local-aiarxiv-cs-lg

MIDAS: Multi-LLM Iterative Data-Adaptive Summarization

arXiv:2608.04307v1 Announce Type: cross Abstract: Text summarization is deceptively difficult. While condensing information seems straightforward, real-world enterprise summarization of support ticket

applicationsarxiv-cs-ai

Neurocomputational Mechanisms of Syntactic Transfer in Bilingual Sentence Production

arXiv:2601.18056v2 Announce Type: replace Abstract: We discuss the benefits of incorporating oscillatory neural mechanisms into the study of bilingual production errors and their traditionally documen

applicationsarxiv-cs-cl

Non-Stationary Inventory Control with Lead Times

arXiv:2602.05799v2 Announce Type: replace-cross Abstract: We study non-stationary single-item, periodic-review inventory control problems in which the demand distribution is unknown and may change ove

safetyarxiv-cs-lg

NSF-HRPT: Neural Semantic Field meets Hierarchical Risk Perception Tree for Safety-Critical Scenario Assessment

arXiv:2608.04776v1 Announce Type: new Abstract: The ability to accurately assess and anticipate risks in safety-critical scenarios is crucial for autonomous driving systems. While existing research ha

OneDayAgent: Towards a Long-Horizon Harness for Autonomous Agents

arXiv:2608.05013v1 Announce Type: cross Abstract: LLM agents are increasingly applied to open-ended everyday requests that span work, study, and life. These tasks are long-horizon, cross-environment,

agentsarxiv-cs-ai

Predicting Brain Morphometry with MT-GNN: Mesh Evolution in Continuous Time with Graph-Based Metric Tensor Embeddings

arXiv:2608.05132v1 Announce Type: new Abstract: Predicting how a subcortical structure's shape will evolve from a few prior scans could support prognosis and clinical-trial enrichment. Existing longit

Privileged, but Biased: How PI-Conditioned Teachers Break Self-Distillation

arXiv:2608.04794v1 Announce Type: new Abstract: Self-distillation (SD) has emerged as a compute-efficient alternative to reinforcement learning with verifiable rewards: a self-teacher, conditioned on

Reasoning Core: Designing Broad Procedural Data for Completion-Supervised Reasoning Training

arXiv:2608.05148v1 Announce Type: new Abstract: Procedural generators produce useful verifiable reasoning problems at scale, but have received less attention as data for completion-supervised fine-tun

Reinforcement Learning and Consumption-Savings Behavior

arXiv:2510.20748v2 Announce Type: replace-cross Abstract: This paper demonstrates how reinforcement learning can explain two puzzling empirical patterns in household consumption behavior during econom

Revealed Rationality: Label-Free Evaluation and Regularization from Representation Theorems

arXiv:2608.05015v1 Announce Type: cross Abstract: Representation theorems in decision theory establish that behavior satisfies certain axioms if and only if it can be rationalized by a well-defined ob

Searching for Sound-Meaning Collisions: Graph-Based Affordance Retrieval and Multi-Evaluator Ranking for Pun Translation at CLEF 2026 JOKER Task 2

arXiv:2608.04299v1 Announce Type: new Abstract: Fifteen years ago, Low proposed that pun translators should stop searching for equivalent words and instead search for new points of contact between sou

Spend Bits Where Queries Look: KV Cache Vector Quantization with Attention-Preserving Transforms

arXiv:2608.04074v1 Announce Type: cross Abstract: Long-context LLM decoding reads the key-value (KV) cache at every step. Loading it takes longer than computing attention over it, so throughput is ban

Tutorials

SurgNarrator: A Generative Retrieval Framework for Surgical Video Understanding

arXiv:2608.04676v1 Announce Type: new Abstract: Surgical procedures unfold as structured and recurring clinical events, whose real-time understanding via intraoperative surgical videos is critical for

tutorialsarxiv-cs-cv

Terminal Agents Suffice for Enterprise Automation

arXiv:2604.00073v3 Announce Type: replace-cross Abstract: There has been growing interest in building agents that can interact with digital platforms to execute meaningful enterprise tasks autonomousl

agentsarxiv-cs-ai

Towards End-to-End Multilingual Metaphor Processing: Integrating Detection, Translation, and Evaluation

arXiv:2608.04260v1 Announce Type: new Abstract: Metaphorical language remains a major challenge for multilingual natural language processing because successful interpretation and translation require r

Traceable LLM-Generated Hazard Scenarios for Operational Safety Analysis of Aviation Systems Using ASRS Reports

arXiv:2608.04697v1 Announce Type: new Abstract: Operational hazard analysis of aviation system operations must consider interactions among weather, ATC actions, airspace constraints, aircraft operatio

VoxStruct3D: Structure-Leading Flow Matching for Voxel-Space 3D MRI Synthesis

arXiv:2608.04557v1 Announce Type: new Abstract: High-fidelity 3D MRI synthesis requires both globally coherent anatomy and fine-grained voxel-level detail. Although latent diffusion makes volumetric g

safetyarxiv-cs-cv

Accelerating Human-Aware Robot Trajectory Generation via Diffusion and Consistency Distillation

arXiv:2608.03159v1 Announce Type: new Abstract: This research proposes a constrained motion planning framework for robot manipulators in human-robot interaction (HRI). For a non-redundant manipulator

safetyarxiv-cs-ro

AnchorKV: Anchor-Residual KV Cache Compression

arXiv:2608.02901v1 Announce Type: cross Abstract: The key-value (KV) cache is the primary memory bottleneck in long-context LLM inference. Existing approaches attack it from opposite ends: eviction me

CausalOPD: First-Wrong-Step Supervision for Distilling Causal Chain Reasoning

arXiv:2608.03673v1 Announce Type: new Abstract: Many critical reasoning tasks, including clinical diagnosis, legal judgment, and industrial fault diagnosis, require step-dependent causal chains in whi

safetyarxiv-cs-lg

CIGTSurv: Clinical Information Guided Tri-modal Survival Prediction with Local Prototype Association and Global Feature Alignment

arXiv:2608.03247v1 Announce Type: cross Abstract: Multimodal learning has significantly advanced survival prediction by integrating pathology images with genomic data. However, clinical information, d

local-aiarxiv-cs-cl

Computing Actual Causes for Neural Network Predictions under Structured Causal Inputs

arXiv:2608.03772v1 Announce Type: new Abstract: Explaining the predictions of neural networks is a central challenge in trustworthy AI. Existing explanation methods, such as those based on feature att

applicationsarxiv-cs-ai

CRS-Triage: Confidence- and Reliability-Aware Selective Triage under Incomplete Clinical Evidence

arXiv:2608.03862v1 Announce Type: new Abstract: Emergency triage requires reliable decisions within a short time period. However, the available electronic health record (EHR) data, including structure

researcharxiv-cs-lg

Design-Time Optimization of Deep Neural Networks for Intermittent Learning on Microcontrollers

arXiv:2608.03589v1 Announce Type: new Abstract: We present a method for designing deep neural networks (DNNs) for intermittent, energy-autonomous, on-device learning on microcontroller units (MCUs). I

local-aiarxiv-cs-lg

Don't Peek at the Answer: Outcome-Masked Group Relative Policy Optimization for Label-Free RLVR

arXiv:2608.03119v1 Announce Type: new Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) improves LLM reasoning but typically relies on ground-truth (GT) answers, limiting scalability. Vo

EvoHIL: Self-Evolving Reward and Flow-Matched Policy Optimization for Robust Human-in-the-Loop Reinforcement Learning

arXiv:2608.03872v1 Announce Type: new Abstract: Human-in-the-loop reinforcement learning (HIL-RL) enables robots to learn contact-rich manipulation from limited real-world interaction, but deployment

safetyarxiv-cs-ro

Fast Object Removal Attacks on Safety-Critical Video-based Perception Systems

arXiv:2608.02806v1 Announce Type: cross Abstract: By leveraging data from video-based perception systems, intelligent transportation systems (ITS) support safety-critical applications that improve roa

safetyarxiv-cs-cv

FedRings: A Scalable and Topology-Aware Federated Learning Framework for LEO Satellite Constellations

arXiv:2608.03436v1 Announce Type: cross Abstract: Federated learning over low Earth orbit (LEO) satellite networks is limited by frequent link changes, short contact times, and a highly dynamic topolo

researcharxiv-cs-lg

Frequency-Decorrelated Temporal Ensembles for EEG--fNIRS Imagined-Handwriting Decoding

arXiv:2608.03176v1 Announce Type: new Abstract: Imagined handwriting offers a temporally rich paradigm for non-invasive neural decoding, yet reliable recognition across unseen participants remains dif

GeoID-PINN: Identifiability-Aware Regional Epidemic Inference with Geographic Coupling

arXiv:2608.02633v1 Announce Type: new Abstract: Regional surveillance data reflect local transmission, reporting, seeding, and external infection pressure, which are difficult to identify separately.

local-aiarxiv-cs-lg

Hear to See: Discerning Stateful Listening for Audio-Visual Instance Segmentation

arXiv:2608.03264v1 Announce Type: cross Abstract: Audio-visual instance segmentation (AVIS) requires accurately identifying and tracking individual sounding objects with pixel-level masks. Existing me

Hardware

Learning and Clustering on Temporal Graphs: Principles, Primitives, and Pooling

arXiv:2608.03696v1 Announce Type: new Abstract: This work focuses on the problem of learning on temporal graphs, with particular emphasis on the task of clustering: obtaining coarse-grained representa

hardwarearxiv-cs-lg

Learning Attribute-aware Representations for Few-shot Scene Text Segmentation

arXiv:2504.11164v2 Announce Type: replace Abstract: Supervised scene text segmentation has achieved notable progress in recent years. However, its development is largely constrained by the scarcity of

safetyarxiv-cs-cv

Multimodal Plant Root Phenotyping with Integration of 3D Skeleton Extraction and Language Analysis

arXiv:2608.03109v1 Announce Type: new Abstract: Plant root phenotyping is fundamental to understanding below-ground structures, optimizing crop management, and improving agricultural sustainability. T

NanoMorph-3D: An End-to-End Physics-Driven Unrolling Framework for Nanomaterial Reconstruction

arXiv:2608.03257v1 Announce Type: new Abstract: Precise 3D characterization of nanomaterials is essential for unlocking structure-property relationships. However, standard electron tomography is funda

local-aiarxiv-cs-cv

PAMT: Process-Aligned Reinforcement Learning for Multi-Domain Machine Translation

arXiv:2608.03077v1 Announce Type: new Abstract: Multi-domain machine translation (MDMT) requires more than fluent generation: it demands domain-sensitive translation decisions such as domain disambigu