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arXiv:2607.24601v1 Announce Type: cross Abstract: Background: Large language models (LLMs) are increasingly used to automate code review, but the reasoning behind their decisions remains hard to under

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Research

EventOD: Event-Aware OD Flow Generation via LLM-Guided Semantic Modulation

DGX agent

arXiv:2607.22655v1 Announce Type: new Abstract: Estimating origin-destination (OD) flows under disruptive events is important for disaster response and urban resilience. Existing deep OD models traine

researcharxiv-cs-ai

28 Jul 2026

Every Client Is an Environment: Federated De-confounding for Spatio-Temporal Forecasting

arXiv:2607.24218v1 Announce Type: cross Abstract: Federated learning has emerged as a promising paradigm for spatio-temporal forecasting (STF), enabling collaborative model training without sharing ra

Evolving from Lessons: Skill-Augmented Table Graph Reasoning for Operation-wise Table Question Answering

arXiv:2607.22633v1 Announce Type: new Abstract: Table Question Answering (TableQA) aims to reason over tables to answer user queries. Existing research treats all questions uniformly and evaluates sol

Explainable Reinforcement Learning via Physics-Aware Policy Distillation

arXiv:2607.24672v1 Announce Type: new Abstract: In safety-critical sectors such as robotics and automotive engineering, the deployment of Deep Reinforcement Learning (DRL) is often hindered by the bla

Safety

Face Age Verification Vulnerabilities Under Simple Appearance Manipulations

arXiv:2607.24194v1 Announce Type: new Abstract: Online platforms increasingly rely on automated age estimation systems to enforce minimum-age policies. Focusing on vision-based models designed for thi

safetyarxiv-cs-cv

FedTaste: Topology-Aware Structural Transfer for Multimodal Federated Learning with Missing Modalities

arXiv:2607.23245v1 Announce Type: cross Abstract: Multimodal Federated Learning is often challenged by arbitrary modality missingness and Non-IID data distributions, which lead to severe representatio

FMOPF: Latent Flow Matching with Constraint-Aware Interaction Priors for AC Optimal Power Flow

arXiv:2607.22788v1 Announce Type: cross Abstract: AC optimal power flow determines the minimum-cost generation dispatch under nonlinear power balance constraints and is solved thousands of times daily

Focus Is All You Need: Adaptive Goal-aware Attention Orchestration for Multi-Agent Graph Systems

arXiv:2607.23678v1 Announce Type: new Abstract: Large language models (LLMs) enable autonomous agents for reasoning, planning, and tool use. Recent systems increasingly organize these agents as graphs

agentsarxiv-cs-ai

Safety

From Camera-Based Sensing to Reasoning: A Comprehensive Review Toward Proactive Vulnerable Road User Safety

arXiv:2510.03314v2 Announce Type: replace-cross Abstract: Ensuring the safety of vulnerable road users (VRUs), such as pedestrians and cyclists, remains a critical challenge, as conventional infrastru

safetyarxiv-cs-ai

gamma-Bridge: A Look-Parametric Diffusion Bridge

model-releasesarxiv-cs-cv

arXiv:2607.22719v1 Announce Type: new Abstract: Multiplicative Gamma noise is a signal-dependent degradation in coherent imaging; synthetic aperture radar (SAR) despeckling is its most prominent real-

Tutorials

Gaze-to-text Generation: Beyond Categorical Decoding of Human Attention

arXiv:2607.23917v1 Announce Type: new Abstract: We introduce a novel learning problem: decoding gaze into natural language descriptions of human goals across diverse visual tasks. Unlike prior work, w

tutorialsarxiv-cs-cv

GEMCo: A Validated, Ethically Releasable Proxy for Inaccessible Counselling Data

arXiv:2607.23621v1 Announce Type: new Abstract: This paper presents GEMCo, a releasable, human-written proxy for inaccessible counselling data: 86 complete German e-mail counselling conversations (728

HydroAgent: Formalizing Forecaster Expertise into Skill-Orchestrated Flood Forecasting Workflows

arXiv:2607.23983v1 Announce Type: cross Abstract: Operational flood forecasting depends on tacit forecaster expertise that is difficult to formalize, audit, and transfer. Although artificial intellige

agentsarxiv-cs-lg

Impute On-Demand: Adaptive Correlated Time Series Imputation for Changing Environments

arXiv:2607.23503v1 Announce Type: cross Abstract: Internet of Things (IoT) applications generate vast amounts of Correlated Time Series (CTS) data that often contain missing values and require imputat

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

Applications

IndicTalk: A Large-Scale Persona-Based Multilingual Conversational Corpus for Indic Languages

arXiv:2607.23242v1 Announce Type: new Abstract: Large Language Models (LLMs) have transformed conversational AI, yet high-quality multilingual code-mixed dialogue resources remain scarce, particularly

applicationsarxiv-cs-cl

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

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

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

Keyword Matters: Unveiling the Energy Sensitivity of On-Device LLM Prompting

arXiv:2607.22568v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly deployed on mobile and embedded devices to improve privacy and reduce network latency. Yet on-device infer

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

Safety

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

LoRA for Gender-Inclusive Rewriting and Activation Steering for Counter-Narrative Generation

arXiv:2607.23083v1 Announce Type: new Abstract: Gender-inclusive language generation seeks to transform biased text into inclusive alternatives while preserving semantic meaning and contextual coheren

LowAux-RDNet: Low-Pass Residual Supervision with Scene-Balanced Real-World Training for Single-Image Reflection Removal

model-releasesarxiv-cs-cv

arXiv:2607.22707v1 Announce Type: new Abstract: Single-image reflection removal aims to recover a clean transmission layer from one image captured through glass. We study an explicit decomposition pip

MARS: Multi-hop Adaptive Retrieval and SPARQL Generation for KGQA

arXiv:2607.14561v2 Announce Type: replace Abstract: Large language models (LLMs) have demonstrated strong reasoning performance, but their tendency to hallucinate limits their reliability in knowledge

agentsarxiv-cs-cl

Maximum Satisfiability of Simple Temporal Problems

arXiv:2607.23785v1 Announce Type: cross Abstract: The Simple Temporal Problem (STP) is a core framework for quantitative temporal constraints. As STP data can be inconsistent, we study MAXSTP: compute

MemVLN: Episodic and Procedural Memory for Vision-and-Language Navigation

arXiv:2607.23504v1 Announce Type: new Abstract: Vision-and-Language Navigation in Continuous Environments (VLN-CE) requires agents to maintain long-horizon visual history for trajectory consistency wh

researcharxiv-cs-cv

Multivariate Time Series Forecasting with Adaptive Non-Local Observables

arXiv:2607.24399v1 Announce Type: cross Abstract: Multivariate time series forecasting (MTSF) predicts future values of multiple variables from historical data. While quantum neural networks have been

Neonatal Hypoxic-ischaemic Encephalopathy Classification from the EEG and HRV Signals Using a Conformer based Masked Autoencoder

arXiv:2607.23554v1 Announce Type: cross Abstract: In this paper, we propose the MAEConformer, a novel self-supervised learning framework that combines the Conformer architecture with the Masked Autoen

Neural Network-Driven Volatility Drag Mitigation under Aggressive Leverage

arXiv:2607.23068v1 Announce Type: cross Abstract: This paper introduces a compact reformulation of a modular end-to-end neural network for global minimum-variance portfolio optimization that decouples

Opti-Q: A Constraint-Based Optimization Framework for Multi-LLM Question Planning

arXiv:2607.22621v1 Announce Type: new Abstract: While large language models (LLMs) enable strong question answering (QA), budgeted deployment is complicated by nondeterminism and heterogeneous resourc

PAC-DP: PAC-Bayesian Diffusion Policy Learning

model-releasesarxiv-cs-ro

arXiv:2607.24296v1 Announce Type: new Abstract: Diffusion Policies (DPs) are able to perform complex manipulation tasks. However, DPs are typically trained by minimizing a denoising objective, which p

Tutorials

Patient-Agnostic Synthetic Pretraining for Efficient Patient-Specific Intraoperative 2D/3D Registration

arXiv:2607.23343v1 Announce Type: cross Abstract: Intraoperative 2D/3D registration aligns preoperative CT volumes with intraoperative X-ray or fluoroscopic images and is essential for image-guided in

tutorialsarxiv-cs-ai

PatiGonit22K: A Comprehensive Dataset for Solving Complex Bengali MWPs

arXiv:2607.22859v1 Announce Type: new Abstract: Mathematical Word Problems (MWPs) are an important benchmark for evaluating natural language understanding and quantitative reasoning. Despite recent pr

Pointer-Augmented Autoregressive Generation of Patent Claims with Joint Topology and Content Decoding

arXiv:2607.24040v1 Announce Type: new Abstract: Autoregressive decoders emit flat token sequences and cannot enforce hierarchical constraints across output segments, a limitation that becomes acute in

Practical advantage beyond the quadratic speedup limit with fully-quantum walks

arXiv:2607.22818v1 Announce Type: cross Abstract: We introduce a new class of fully-quantum Metropolis walks in which both the proposal and acceptance steps are intrinsically quantum. Unlike standard

PRESTO: Prefix-Aligned Tree Drafting for Diffusion Speculative Decoding

arXiv:2607.22634v1 Announce Type: new Abstract: Diffusion Large Language Models (dLLMs) have emerged as a promising alternative to autoregressive (AR) LLMs, generating tokens in parallel. This makes t

Risk reversal for least squares estimators under nested convex constraints

arXiv:2601.16041v2 Announce Type: replace-cross Abstract: In constrained stochastic optimization, one expects that restricting the feasible set, provided it still contains the true parameter, should n

SetGo: Metadata Readiness for Scientific AI Datasets

arXiv:2607.22677v1 Announce Type: cross Abstract: Scientific datasets intended for AI use require both computational readiness for model training and metadata readiness for discovery, sharing, and reu

agentsarxiv-cs-ai

Share No More Than the Request Requires: Federated Disclosure for Perspective-Aware AI

arXiv:2607.22953v1 Announce Type: new Abstract: Modern AI systems bring societal risks such as mass surveillance, extreme concentrations of power, and loss of user autonomy---calling into question a m

Sparse Autoencoders Encode Both Concepts and Functions: The Downstream Geometry of Feature Effects

arXiv:2607.24645v1 Announce Type: cross Abstract: The wide-scale use of sparse autoencoders (SAEs) as interpretability tools is limited by inconsistent links between SAE features and model behavior. F

SpecBox: Speculative Sandbox Scheduling for Efficient LLM Agent Serving

arXiv:2607.23933v1 Announce Type: cross Abstract: As LLM agents increasingly rely on the Model Context Protocol (MCP) to invoke isolated external sandboxes, disaggregated sandbox deployment introduces

agentsarxiv-cs-ai

StAR: Segment Anything Reasoner

model-releasesarxiv-cs-cv

arXiv:2603.14382v2 Announce Type: replace Abstract: As AI systems are being integrated more rapidly into diverse and complex real-world environments, the ability to perform holistic reasoning over an

SwitchBraidNet: Quantisation-Aware Lightweight Architecture for Hybrid Brain-Computer Interface

arXiv:2606.18816v2 Announce Type: replace-cross Abstract: Hybrid brain-computer interfaces (BCIs) that integrate motor imagery (MI) and steady-state visual evoked potentials (SSVEP) provide high-dimen

TLRNet: Estimating Individual Treatment Effect based on Local Information and Single Learner Structure

arXiv:2607.22762v1 Announce Type: cross Abstract: Causal inference has become a central issue across various fields, including computer science, statistics, economics, education, healthcare, and medic

Applications

Traceable LLM Reasoning for Fake-Order Fraud Detection

arXiv:2607.23075v1 Announce Type: cross Abstract: Detecting fake-order fraud at scale remains a critical challenge for large online-to-offline (O2O) service platforms, as existing approaches often rel

applicationsarxiv-cs-ai

Transfer learning for conflict and duplicate detection in software requirement pairs

arXiv:2301.03709v3 Announce Type: replace-cross Abstract: Consistent and holistic expression of software requirements is important for the success of software projects. In this study, we aim to enhanc

researcharxiv-cs-lg

Try Once, Then Optimal: De-Redundified Procedure Memory for Cross-Episode Exploration Amortization

model-releasesarxiv-cs-ro

arXiv:2607.23702v1 Announce Type: new Abstract: Manipulating objects with hidden internal state, such as a latched microwave, forces a robot to probe before it can act. Yet a robot that has solved an