Search: “framework”

IMPRINT: Image-Conditioned Query Enrichment for Long-Tail Object Goal Navigation

arXiv:2607.25106v1 Announce Type: new Abstract: Embodied AI increasingly relies on queryable semantic maps built from pre-trained vision-language models to enable zero-shot Object Goal Navigation (Obj

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Improving Rare Medication Recommendation with Counterfactual Data Augmentation and Large Language Models

DGX agent

arXiv:2607.24829v1 Announce Type: cross Abstract: AI-based medication recommendation systems have attracted substantial attention due to their potential to enhance patient safety and therapeutic outco

safetyarxiv-cs-lg

29 Jul 2026

Interactive Reward Agent: GUI Task Evaluation via Environment-State Verification

arXiv:2607.25904v1 Announce Type: new Abstract: Graphical user interface task evaluation aims to determine whether a GUI agent has successfully completed a user instruction. Automated GUI task evaluat

Interpretable Column Annotation with LLM-Symbolized Decision Process Materialization

arXiv:2607.25228v1 Announce Type: new Abstract: Column annotation (CA), including column type annotation (CTA) and column property annotation (CPA), aims to identify the meanings of table columns and

local-aiarxiv-cs-cl

IRIS: Reusable Identity Representations from Frozen LLMs for Entity Alignment

arXiv:2607.25579v1 Announce Type: cross Abstract: Entity alignment (EA) identifies entities across knowledge graphs (KGs) that refer to the same real-world object. Conventional EA methods mainly explo

Joint Text-Audio Alignment for EEG-to-Text Decoding in Chinese Speech Production and Perception

arXiv:2607.25626v1 Announce Type: new Abstract: Decoding speech information directly from scalp electroencephalography (EEG) into text provides a potential non-invasive neural communication pathway fo

Knowledge-Guided Multimodal Reasoning over Interacting Streams for Video-Level Ambivalence and Hesitancy Recognition

arXiv:2607.25961v1 Announce Type: cross Abstract: Ambivalence and hesitancy (A/H) are conflicting affective states that precede the delay or abandonment of health behaviour change. Recognition of A/H

researcharxiv-cs-ai

LaP-Forensics: Latent-Pixel Consistency Guided Multimodal Reasoning for Deepfake Detection

arXiv:2607.25962v1 Announce Type: new Abstract: Recent generative models can produce images with few obvious visual artifacts, weakening detectors and explanations that rely only on surface appearance

Leak-Free Cross-Validated Stacking with Per-Architecture Calibration for Sand-Boil Segmentation in Earthen Levees

arXiv:2607.25367v1 Announce Type: new Abstract: Sand boils, points where water seeping beneath an earthen levee re-emerges at the surface, are early warnings of internal erosion, and deep segmentation

researcharxiv-cs-cv

Learning from Local Walks on Dynamic Graphs with Bandit Feedback

arXiv:2607.10571v2 Announce Type: replace-cross Abstract: We study stochastic multi-armed bandits on dynamic graphs, where arms correspond to the vertices of a network with time-varying edges. In this

LENS: Adaptive Spatio-Temporal Zooming for Keyframe Sampling in Long-Form Videos

arXiv:2607.25125v1 Announce Type: new Abstract: Despite rapid progress in Multi-modal Large Language Models (MLLMs), understanding long-form videos is still bottlenecked by limited context windows. Wh

researcharxiv-cs-cv

LLM as Forecasting Planner: Training-Free Text Conditioning for Time-Series Foundation Models

arXiv:2607.24892v1 Announce Type: cross Abstract: Text-conditioned time-series forecasting predicts a series from both its numerical history and natural-language context, allowing forecasts to account

M^2PO: Multi-Perspective Multi-Pair Preference Optimization for Machine Translation

arXiv:2510.13434v2 Announce Type: replace Abstract: Aligning Large Language Models (LLMs) with human preferences is pivotal for Machine Translation (MT), yet current approaches are often hindered by m

Agents

Machine Intelligence on the Edge: Interpretable Cardiac Pattern Localisation Using Reinforcement Learning

arXiv:2508.21652v2 Announce Type: replace-cross Abstract: Matched filters are widely used to localise signal patterns due to their high efficiency and interpretability. However, their effectiveness de

agentsarxiv-cs-lg

Agents

Matryoshka Agent: Unfolding Sub-Agents for Long-Horizon Machine Learning Engineering

arXiv:2607.25090v1 Announce Type: new Abstract: Machine learning engineering (MLE) tasks require long-horizon decision making over iterative solution debugging and refinement, under expensive and feed

agentsarxiv-cs-ai

Mechanisms of Width Scaling in Normalized Residual Networks: The Effective Alignment Dimension

arXiv:2607.24887v1 Announce Type: cross Abstract: Existing theories of neural-network width characterize asymptotic limits, but provide limited guidance on whether an expansion direction identified fr

Med-SegLens: Latent-Level Model Diffing for Interpretable Medical Image Segmentation

arXiv:2602.10508v2 Announce Type: replace Abstract: Modern segmentation models achieve strong predictive performance but remain largely opaque, limiting our ability to diagnose failures, understand da

safetyarxiv-cs-cv

Applications

MEDIC-AD: Towards Medical Vision-Language Model's Clinical Intelligence

arXiv:2603.27176v2 Announce Type: replace Abstract: Lesion detection, symptom tracking, and visual explainability are central to real-world medical image analysis, yet current medical Vision-Language

applicationsarxiv-cs-cv

MedJudgeRAG: Option-Wise Evidence Judgment with Dynamic Knowledge Graphs for Medical MCQA

arXiv:2607.24838v1 Announce Type: cross Abstract: In medical multiple-choice question answering (MCQA), Retrieval-Augmented Generation (RAG) can supplement the domain knowledge of language models (LMs

Multi-Objective Kinodynamic Motion Planning with Asymptotic Pareto Optimality

arXiv:2607.15508v2 Announce Type: replace Abstract: In this paper, we address the challenge of multi-objective motion planning for systems under kinodynamic constraints. We consider three problem clas

researcharxiv-cs-ro

Multimodal Hybrid Retrieval-Augmented Generation for Scientific Document Understanding using Open-Source SLMs

arXiv:2607.24799v1 Announce Type: cross Abstract: Large Language Models tend to hallucinate when answering domain-specific ques tions from scientific documents without prior fine-tuning. Currently, me

MusiChat: Vibe Composing for Music Creation

arXiv:2607.24873v1 Announce Type: new Abstract: Recent advances in AI music generation have enabled users to create complete musical pieces from natural-language prompts. However, most existing system

researcharxiv-cs-ai

MyoCardBench: A Real-World Data Benchmark for Evaluating Large Language Models in Clinically Authentic Cardiovascular Care Scenarios

arXiv:2607.25186v1 Announce Type: new Abstract: Background: Most medical large language model (LLM) benchmarks focus on examination knowledge or isolated tasks and may not reflect the longitudinal, mu

ODYSSE: Episode-wise Policy Optimization for Personalized Agentic Reasoning

arXiv:2607.25369v1 Announce Type: new Abstract: Agentic systems have rapidly advanced in their ability to interact with real-world environments, leverage external tools, and provide services for users

OmniDelta: Skill-Driven Budget Allocation for Token Compression in OmniLLMs

arXiv:2607.25669v1 Announce Type: new Abstract: Emerging Omni-modal Large Language Models (OmniLLMs) enable unified understanding of text, audio, and video, but their long audio-video token sequences

local-aiarxiv-cs-ai

OmniPhys: Knowledge-Graph-Driven Benchmarking and Collective Optimization for Physical Commonsense in Text-to-Image Generation

arXiv:2607.25641v1 Announce Type: cross Abstract: While text-to-image models exhibit remarkable visual fidelity, they frequently violate fundamental physical commonsense. Existing benchmarks often rel

Tutorials

On the Design and Evaluation of Human-centered Explainable AI Systems: A Systematic Review and Taxonomy

arXiv:2510.12201v2 Announce Type: replace Abstract: As AI becomes more common in everyday living, there is an increasing demand for intelligent systems that are both performant and understandable. Exp

tutorialsarxiv-cs-ai

On the Use of Synthetic Data for Threshold Calibration in Face Recognition: Performance and Security Implications for Border Control Systems

arXiv:2607.25990v1 Announce Type: new Abstract: The recently deployed Entry/Exit System (EES) introduces large-scale biometric verification into European border control, requiring face recognition sys

safetyarxiv-cs-cv

Online learning of subgrid-scale models for quasi-geostrophic turbulence in planetary interiors

arXiv:2511.14581v2 Announce Type: replace-cross Abstract: Machine learning approaches to subgrid-scale (SGS) modelling are now well established in atmospheric and oceanic applications. Among these, on

researcharxiv-cs-lg

OPERA: Offline Policy-guided Expert Routing and Adaptation for Universal Biomedical Image Analysis

arXiv:2607.25108v1 Announce Type: cross Abstract: Biomedical image analysis spans diverse modalities and tasks, yet real-world deployment is hindered by severe distribution shifts across scanners, pro

Applications

Operational evaluation of data-driven forest fire forecasting models

arXiv:2603.25469v2 Announce Type: replace Abstract: A growing body of literature has focused on predicting wildfire occurrence using machine learning methods, capitalizing on high-resolution data and

applicationsarxiv-cs-lg

Optimal Ansatz-free Hamiltonian Learning In Situ

arXiv:2606.19486v2 Announce Type: replace-cross Abstract: Characterizing the features of a Hamiltonian that governs a quantum system serves as a fundamental subroutine of quantum device calibration, s

researcharxiv-cs-lg

OrganLens: Organ-Specific Representation Learning for CT Foundation Models

arXiv:2607.25164v1 Announce Type: cross Abstract: A CT examination captures multiple organs, but many biomedical questions concern abnormalities, prognosis, or longitudinal change in a specific organ.

researcharxiv-cs-ai

OrthKD: Extracting Generalized Clinical Knowledge from Heterogeneous Teachers for Lightweight Deployment

arXiv:2607.25545v1 Announce Type: cross Abstract: Deploying diabetic retinopathy (DR) screening models in primary care requires edge-efficient systems that remain accurate, safe, and reliable under do

P3: Probabilistic Policy Propagation for Stable VAE-Based Robot Learning

arXiv:2607.25541v1 Announce Type: new Abstract: Variational Autoencoders are widely used to encode high-dimensional and noisy observations in robotics. However, their stochastic latent creates a misma

safetyarxiv-cs-ro

PanoLess: Environment Reconstruction from Partial Reflective Views

arXiv:2607.25362v1 Announce Type: new Abstract: Reflections from shiny objects and glass facades naturally extend the field of view of a camera, capturing the surrounding environment without the need

Penelope: Localized Latent Recurrence for Efficient Structured Reasoning

arXiv:2607.25915v1 Announce Type: new Abstract: Complex structured reasoning tasks often require additional computation, yet current language models obtain it mainly by increasing parameter scale or b

Physics-Informed CNN-LSTM for Street-Scale Urban Flood Prediction: Reconciling Aggregate Accuracy and Street-Level Plausibility

arXiv:2607.25148v1 Announce Type: new Abstract: Deep learning surrogate models trained with mean-squared-error loss produce statistically accurate but physically unconstrained flood predictions: water

local-aiarxiv-cs-lg

Applications

Physics of Language Models: Part 4.1, Architecture Design and the Magic of Canon Layers

arXiv:2512.17351v2 Announce Type: replace Abstract: Understanding architectural differences in language models is challenging, especially at academic-scale pretraining (e.g., 1.3B parameters, 100B tok

applicationsarxiv-cs-cl

PIcsC: Partitioning-Induced Covariate Shift Correction

model-releasesarxiv-cs-lg

arXiv:2607.25441v1 Announce Type: new Abstract: Covariate shift across training-data partitions biases model selection and parameter estimation in cross-validation, lifelong learning, and federated le

PilotRL: Training Language Model Agents via Global Planning-Guided Progressive Reinforcement Learning

arXiv:2508.00344v5 Announce Type: replace Abstract: Large Language Models (LLMs) have shown remarkable advancements in tackling agent-oriented tasks. Despite their potential, existing work faces chall

Predictive Control for Driving under Uncertain Road Geometry Estimated from Onboard Vision

arXiv:2508.02494v2 Announce Type: replace-cross Abstract: Autonomous vehicles driving on unknown roads must estimate the road geometry from onboard sensors and follow the resulting reference while res

safetyarxiv-cs-ro

RDQ: Residual Distribution Quantization for Large Language Models

model-releasesarxiv-cs-lg

arXiv:2607.10137v2 Announce Type: replace Abstract: Post-training quantization (PTQ) of large language models degrades sharply below 4-bit precision. We identify the root cause as residual stream dist

ReDesign: Recovering Editable Design Structures from Images via Agentic Decomposition

arXiv:2607.25565v1 Announce Type: new Abstract: Recovering an editable design file from a raster image is a common and costly bottleneck in modern design workflows, yet remains challenging since edita

ReLATE: Reliability-Guided Evidence Fusion for Robust UAV--Satellite cross-view Geo-Localization

arXiv:2607.25524v1 Announce Type: cross Abstract: Unmanned aerial vehicle (UAV)-satellite cross-view geo-localization matches UAV images against satellite imagery and has achieved impressive accuracy

REPREC: Representation Driven Parameter-Efficient Recommendation System

arXiv:2607.24845v1 Announce Type: cross Abstract: Large language models (LLMs) have been applied to sequential recommendation by formulating it as a natural language task. Previous work has improved p

SAGE: Stochastic Prompt Optimization via Agent-Guided Exploration

arXiv:2606.18902v2 Announce Type: replace Abstract: Context engineering has emerged as a primary lever for improving AI systems without parameter updates. Recent work showing that textual gradients do

SAM3D-Guided Object-Centric Representation Alignment for Vision-Language-Action Models

arXiv:2607.25912v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models have shown strong potential for general robot manipulation, but most existing models rely on 2D visual-language ba

local-aiarxiv-cs-ai