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FlashPDE: A Drop-In Fused Triton Operator Library for Neural PDE Solvers

model-releasesarxiv-cs-lg

arXiv:2607.18020v2 Announce Type: replace Abstract: Physics-Informed Neural Networks (PINNs) solve PDEs by incorporating physical constraints into neural-network training, but large-scale problems are

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Research

FlowEdit: Information-Theoretic Control of LLM Reasoning Flows for Ill-posed Problems Involving Conflicts

DGX agent

arXiv:2607.20500v1 Announce Type: new Abstract: Large Language Models (LLMs) perform strongly on well-specified reasoning tasks with a feasible answer. However, problems encountered in the open world

researcharxiv-cs-ai

24 Jul 2026

Tutorials

Focus on What Matters: Constraining Spatial-Temporal Attention via Action-Units for Noise-Resilient AQA

arXiv:2511.05611v2 Announce Type: replace Abstract: The core challenge in Action Quality Assessment (AQA) lies in extracting fine-grained motion features from redundant and complex video backgrounds.

tutorialsarxiv-cs-cv

FORGE-plus: Force-Budgeted Recovery for Contact-Rich Assembly with a Frozen LLM Supervisor

arXiv:2607.21227v1 Announce Type: new Abstract: Force-conditioned reinforcement learning (RL) enables tight-clearance assembly under a commanded force ceiling, but practical deployment requires determ

Foundation-model-guided radiogenomic discovery linking cancer genomes to cancer scans

arXiv:2607.20583v1 Announce Type: cross Abstract: The function of many genes is still unknown, and conventional driver-discovery methods, which rely on how frequently a gene is mutated, cannot assess

Free energy landscape of Dense Associative Memory

arXiv:2607.19195v2 Announce Type: replace-cross Abstract: Using large deviations theory, we solve and obtain a general expression for the free energy functional for a broad class of associative memori

From a Word-Level Dictionary to Sentence-Level Semantics: Multilingual Grievance Labelling with Contextual Models

model-releasesarxiv-cs-cl

arXiv:2607.20946v1 Announce Type: new Abstract: Grievance is one of the warning signs analysts look for when assessing threats of violence. It is increasingly measured at scale from online text, most

From Agent Failures to Text Policies: What Works and What Breaks

arXiv:2607.20668v1 Announce Type: cross Abstract: TextGrad improves language-model systems by revising text from feedback. Its core thesis is that natural-language feedback can act as a gradient for o

From Atoms to Entropy: Optimal Noise Allocation for Diffusion Training in the Convex Regime

arXiv:2607.20540v1 Announce Type: cross Abstract: How should a diffusion model decide which noise levels to train on, and how much? Despite the importance of this choice, current noise schedules are b

From Attention to Frequency: Integration of Vision Transformer and FFT-ReLU for Enhanced Image Deblurring

arXiv:2511.10806v1 Announce Type: cross Abstract: Image deblurring is vital in computer vision, aiming to recover sharp images from blurry ones caused by motion or camera shake. While deep learning ap

Agents

From Chatbot to Digital Colleague: The Paradigm Shift Toward Persistent Autonomous AI

arXiv:2606.14502v2 Announce Type: replace Abstract: Large Language Models (LLMs) are undergoing a fundamental transformation from conversational generators into integrated AI systems capable of reason

agentsarxiv-cs-ai

From Checklists to Clusters: A Homeostatic Account of AGI Evaluation

arXiv:2510.15236v2 Announce Type: replace Abstract: Contemporary AGI evaluations report multidomain capability profiles, yet they typically assign symmetric weights and rely on snapshot scores. This c

Local Ai

From Dependency to Compositionality: A Neurosymbolic Lifting of LLM Outputs via Combinatory Categorial Grammar

arXiv:2607.18961v2 Announce Type: replace Abstract: Large language models (LLMs) generate fluent text by incrementally predicting the next token from a prefix. Critics in the generative tradition argu

local-aiarxiv-cs-ai

From Errors to Rules: Iterative Prompt Optimization for Text Classification

arXiv:2607.20497v1 Announce Type: new Abstract: Prompt optimization for text classification spans diverse approaches, from demonstration selection to exploration-based search to error-driven diagnosis

From Evaluation to Optimisation: Hierarchy-Aware Training Signals for CWE Prediction in Python

model-releasesarxiv-cs-lg

arXiv:2607.21069v1 Announce Type: new Abstract: The original ALPHA benchmark introduced a taxonomy-aware penalty for evaluating CWE-level vulnerability prediction in Python and proposed that the penal

From Noise to Diversity: Random Embedding Injection in LLM Reasoning

arXiv:2605.11936v2 Announce Type: replace Abstract: Recent soft prompt research has tried to improve reasoning by inserting trained vectors into LLM inputs, yet whether the gain comes from the learned

Applications

From Resource Flow to Executable Tests: Petri-Net-Guided LLM Test Generation for Concurrent Stateful Rust APIs

arXiv:2607.21530v1 Announce Type: cross Abstract: Concurrent stateful library APIs expose behavior through evolving resource ownership, lifecycle states, and competing interleavings. Large language mo

applicationsarxiv-cs-ai

From Scalars to Time Series: Rethinking Implicit Neural Representations for Time-Varying Volumetric Data

arXiv:2607.20970v1 Announce Type: new Abstract: Implicit neural representations (INRs) for time-varying volumetric data are typically trained using dense sampling over spatiotemporal coordinates, wher

From Static Bibliometrics to Dynamic Knowledge Graphs: An LLM-Powered Framework for Modernizing Science, Technology, and Innovation (STI) Analytics

arXiv:2607.21327v1 Announce Type: cross Abstract: Bibliometric indicators - citation counts, h-indexes, co-authorship networks - have long anchored science, technology, and innovation (STI) analytics,

Frontier Financial Judgement: Can agents tell what might move a stock?

arXiv:2607.20645v1 Announce Type: cross Abstract: We introduce Frontier Financial Judgement, a challenging new benchmark developed in collaboration with professional equity analysts to assess agents'

FSB-Net: Frequency-Spatial Boundary Network for Brain Stroke Lesion Segmentation in Non-Contrast CT

arXiv:2607.20955v1 Announce Type: new Abstract: Accurate segmentation of brain stroke lesions in non-contrast computed tomography (NCCT) scans is critical for rapid clinical decision-making, yet remai

researcharxiv-cs-cv

Future Rendering neq Future Surface: A Benchmark and Dataset for Dynamic Surface Reconstruction Beyond the Observed Window

model-releasesarxiv-cs-cv

arXiv:2607.21471v1 Announce Type: new Abstract: Dynamic-scene reconstruction is almost always evaluated inside the observed time window, yet deployment settings such as AR overlays, robot interaction,

GaugeQuant: Online Learning of Quantization-Optimal Bases from LLM Symmetries

model-releasesarxiv-cs-cl

arXiv:2607.20757v1 Announce Type: cross Abstract: Transformers are known to have internal continuous symmetries that leave outputs invariant, while modifying quantization. GaugeQuant leverages this in

Generative AI and Agency in Education: A Critical Scoping Review and Thematic Analysis

arXiv:2411.00631v2 Announce Type: replace-cross Abstract: This scoping review examines the relationship between Generative AI (GenAI) and agency in education, analyzing the literature available throug

Generative Artificial Intelligence in Bioinformatics: A Systematic Review of Models, Applications, and Methodological Advances

arXiv:2511.03354v2 Announce Type: replace-cross Abstract: Generative artificial intelligence (GenAI) is transforming bioinformatics by advancing genomics, proteomics, transcriptomics, structural biolo

Applications

Generative Bayesian Filtering for State Estimation

arXiv:2607.20521v1 Announce Type: new Abstract: The state of a dynamic system evolves over time, switching among several latent modes that govern its observable behavior. Filtering methods infer the l

applicationsarxiv-cs-lg

Geo3R: Mitigating Spatial Reasoning Hallucination in Multimodal Large Language Models

arXiv:2607.21085v1 Announce Type: new Abstract: Despite remarkable progress in visual understanding, Multimodal Large Language Models (MLLMs) remain prone to hallucinations when reasoning about spatia

researcharxiv-cs-cv

Geometric Configurations of Perturbed Jailbreak Prompts

arXiv:2607.20581v1 Announce Type: cross Abstract: Perturbation techniques that turn unsuccessful jailbreak prompts into successful ones are continuously evolving, constituting a major security threat

GeoThreat: Transferable Targeted Adversarial Attacks on Large Vision-Language Models for Remote Sensing Image Interpretation

arXiv:2607.21036v1 Announce Type: new Abstract: Adversarial attacks against large vision-language models (LVLMs) serve as an effective means of assessing their robustness in cross-modal semantic under

researcharxiv-cs-cv

GeoWorldAD: Geometry World Action Model for Autonomous Driving

arXiv:2607.17521v2 Announce Type: replace Abstract: Autonomous driving requires both safe and efficient planning decisions in dynamic 3D environments. Although recent Vision/Video-Action models learn

Gibbs randomness-compression proposition

arXiv:2505.23869v5 Announce Type: replace-cross Abstract: A proposition that connects randomness and compression is put forward via Gibbs entropy over set of measurement vectors associated with a loss

researcharxiv-cs-lg

GigaPath-Flash and GigaTIME-Flash: Efficient Pathology Foundation Models for Whole-Slide and Tumor Microenvironment Analysis

arXiv:2607.18218v2 Announce Type: replace-cross Abstract: Foundation models have emerged as a driving force in computational pathology, with the potential to transform cancer diagnosis, prognosis, and

GLAM-SLAM: Real-time Gaussian Large-scale Mapping via Flow Densification and Spatial Decomposition

arXiv:2607.21416v1 Announce Type: cross Abstract: Existing Gaussian-splatting-based monocular Simultaneous Localization and Mapping (SLAM) systems are either tailored to short sequences, are not real-

safetyarxiv-cs-cv

GLAN-QnA-KR: A Seedless Taxonomy-Driven Korean Instruction Corpus

model-releasesarxiv-cs-cl

arXiv:2607.20443v1 Announce Type: new Abstract: We release GLAN-QnA-KR, a 303,581-row openly redistributable Korean instruction-QA corpus produced via the seedless taxonomy-driven GLAN synthesis pipel

GlucoTune: A Unified Framework for Blood Glucose Preprocessing, Forecasting, and Benchmarking in Diabetes

arXiv:2607.21117v1 Announce Type: cross Abstract: Preprocessing blood glucose time-series data is a critical yet often overlooked step in developing data-driven methods for diabetes management, partic

GPE: Evaluating Robust Evidence Aggregation for Fact Verification under Controllable GEO-Style Poisoning

arXiv:2607.20730v1 Announce Type: cross Abstract: Large language models increasingly use search tools to retrieve up-to-date information, introducing a new attack surface in which retrieved documents

Gradient Concentration, Not Weight Saliency, Explains Representation-Level Class Unlearning

model-releasesarxiv-cs-lg

arXiv:2607.21353v1 Announce Type: new Abstract: Machine unlearning aims to remove the influence of specific training data while preserving model utility. Many state-of-the-art approaches pursue this g

Agents

GRADRAG: Cross-Component Prompt Adaptation for Coordinated Multi-Agent RAG

arXiv:2607.21324v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) systems increasingly employ multiple LLM agents. Yet, most prior work optimizes components in isolation rather th

agentsarxiv-cs-ai

GrainGS: Gradient-Decoupled Gaussian Splatting for Efficient Dynamic Novel View Synthesis

model-releasesarxiv-cs-cv

arXiv:2607.21448v1 Announce Type: new Abstract: Dynamic scene reconstruction with 3D Gaussian Splatting requires a balance between fine-grained motion modeling, structural stability, and compact repre

Graph Learning on Ensembles of Cyclic Peptides: An Investigation of Molecular Ensemble Modeling

arXiv:2607.21561v1 Announce Type: new Abstract: Molecular property prediction from structure often uses a single representative conformation, even though many molecules exist as conformational ensembl

researcharxiv-cs-lg

GraphVid: Interactive Graph-Controllable Video Generation

arXiv:2607.21580v1 Announce Type: cross Abstract: Controllable video generation remains challenging due to the difficulty of specifying precise multi-object interactions using text prompts or motion-c

Grasp, Handover, Rotate: Bimanual Object Reorientation via Compositional Diffusion and Energy-Based Optimization

arXiv:2607.21341v1 Announce Type: new Abstract: Bimanual object reorientation - picking an object, handing it over between two arms, and placing it in a desired target pose - is valuable when direct p

Grounding Investor Views: Neural Predicates in the Black-Litterman Model

arXiv:2607.20533v1 Announce Type: cross Abstract: Portfolio construction under the Black-Litterman model requires investors to specify views on asset returns alongside explicit uncertainty estimates -

GroupVideo: Multi-Identity Customized Text-to-Video Generation

arXiv:2607.21027v1 Announce Type: new Abstract: Current identity customized video generation methodologies are predominantly limited to single-identity scenarios, as the lack of explicit identity sepa

safetyarxiv-cs-cv

Agents

GS-Agent: Creating 4D Physical Worlds With Generative Simulation

arXiv:2607.21522v1 Announce Type: cross Abstract: Creating dynamic and physically realistic 4D worlds from natural language descriptions is both fascinating and challenging. Traditional computer graph

agentsarxiv-cs-ai

GuardianAgentBench: Where Agents Fail and How to Guard Them

arXiv:2607.20982v1 Announce Type: new Abstract: As large language model agents increasingly operate autonomously with access to tools and external environments, ensuring their safe and reliable behavi

GuidedAttention: Interpretable and Correctable Visual Attention for OOD-Robust Robot Manipulation via Imitation Learning

arXiv:2607.21049v1 Announce Type: new Abstract: End-to-end visuomotor policies provide little opportunity for humans to understand or correct the policy's visual attention. We propose GuidedAttention,

Tutorials

Gumbel Distillation for Parallel Text Generation

arXiv:2603.22216v2 Announce Type: replace Abstract: The slow, sequential nature of autoregressive (AR) language models has driven the adoption of parallel decoding methods. However, these non-AR model

tutorialsarxiv-cs-cl