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arXiv:2607.03233v1 Announce Type: cross Abstract: The rapid growth of publicly available digital information has rendered manual open-source intelligence (OSINT) analysis insufficient for modern intel

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Auto-AEG: Scalable Data Construction for Open-Vocabulary Audio Event Grounding

DGX agent

arXiv:2607.04383v1 Announce Type: cross Abstract: Large Audio-Language Models (LALMs) reason fluently about sound yet struggle to localize precisely when events occur, while classical Sound Event Dete

model-releasesarxiv-cs-ai

7 Jul 2026

ClinOCR-Bench: A Comprehensive Clinical Scanned Document Dataset for Optical Character Recognition Model Evaluation

arXiv:2607.03650v1 Announce Type: cross Abstract: Extracting textual information from scanned medical documents, such as external laboratory reports and manually filled forms, has been a major challen

CoDoL: Conditional Domain Prompt Learning for Out-of-Distribution Generalization

arXiv:2509.15330v2 Announce Type: replace Abstract: Recent advances in pre-training vision-language models (VLMs), e.g., contrastive language-image pre-training (CLIP) methods, have shown great potent

safetyarxiv-cs-cv

Continual Model Merging with Test-Time Adaptation for Whole-Slide Image Analysis

arXiv:2607.04755v1 Announce Type: new Abstract: Model merging offers a practical alternative to conventional continual learning by integrating independently fine-tuned models without retaining previou

CP-WSP: A Declarative CP-SAT Framework for Configurable Multi-Constraint Workforce Scheduling

arXiv:2607.05177v1 Announce Type: new Abstract: Workforce scheduling is an NP-hard combinatorial optimization problem requiring simultaneous satisfaction of labor regulations, coverage requirements, e

CTForensics: A Comprehensive Dataset and Method for AI-Generated CT Image Detection

arXiv:2603.01878v2 Announce Type: replace Abstract: Recent advances in generative AI have made synthetic Computed Tomography (CT) images increasingly realistic, enabling promising applications in medi

Curriculum-Guided Layer Scaling for Language Model Pretraining

arXiv:2506.11389v4 Announce Type: replace Abstract: As the cost of pretraining large language models grows, there is continued interest in strategies to improve learning efficiency during this core tr

DrugAgent: Reliable Multi-Agent Integration of Conflicting Biomedical Evidence for Drug-Target Interaction Assessment

arXiv:2408.13378v5 Announce Type: replace Abstract: Workflows in drug-target interaction (DTI) assessment require integrating heterogeneous data from predictive models, curated resources, and observat

ELVA: Exploring Ranking-Driven Universal Multimodal Retrieval

arXiv:2606.20280v2 Announce Type: replace-cross Abstract: Leveraging Multimodal Large Language Models (MLLMs) via contrastive learning has become a mainstream paradigm for improving the performance of

Enhancing Video Physical Consistency via Role-aware Joint Training and Modality-decoupled Denoising

arXiv:2607.04653v1 Announce Type: new Abstract: While modern video diffusion models excel in visual fidelity, maintaining long-range physical consistency remains a formidable challenge. Conventional p

Fair-GPTQ: Bias-Aware Quantization for Large Language Models

arXiv:2509.15206v3 Announce Type: replace Abstract: The high memory demands of generative language models have drawn attention to quantization, which reduces memory usage by mapping model weights to l

safetyarxiv-cs-cl

Fun-TSG: A Function-Driven Multivariate Time Series Generator with Variable-Level Anomaly Labeling

arXiv:2604.14221v2 Announce Type: replace Abstract: Reliable evaluation of anomaly detection methods in multivariate time series remains an open challenge, largely due to the limitations of existing b

FuseMamba-VD: Dual Branch VideoMamba with Gated Class Token Fusion for Violence Detection

arXiv:2506.03162v3 Announce Type: replace-cross Abstract: The rapid proliferation of surveillance cameras has increased the demand for automated violence detection. While CNNs and Transformers have sh

GALOSH: Blind, Training-Free Denoising of Raw Bayer and sRGB Images by Parallel-Friendly Local Shrinkage

arXiv:2607.03768v1 Announce Type: cross Abstract: Classical training-free denoisers such as BM3D and non-local means owe much of their strength to search: content-dependent block matching whose memory

GameEngineBench: Evaluating Coding Agents on Real C++ Runtime Environments

arXiv:2607.03525v1 Announce Type: cross Abstract: Game engines provide real-time simulation, rendering, physics, interaction, networking, and asset pipelines, making them valuable not only for games b

How Much of the Routing Gap Is Real? Decomposing the Router-to-Oracle Gap into Reproducible Specialist Advantage and Single-Draw Label Noise

model-releasesarxiv-cs-lg

arXiv:2607.03436v1 Announce Type: new Abstract: Routing among large language models (LLMs) promises better quality at lower cost, motivated by the reported gap between learned routers and a per-instan

Humanoid Everyday: A Comprehensive Robotic Dataset for Open-World Humanoid Manipulation

arXiv:2510.08807v3 Announce Type: replace-cross Abstract: From loco-motion to dextrous manipulation, humanoid robots have made remarkable strides in demonstrating complex full-body capabilities. Howev

safetyarxiv-cs-lg

ICME 2026 Grand Challenge on Cross-Scenario Defect Detection and Fine-Grained Severity Grading for High-Precision Manufacturing

arXiv:2607.04675v1 Announce Type: new Abstract: This paper presents the IEEE International Conference on Multimedia and Expo (ICME) 2026 Grand Challenge on Cross-Scenario Defect Detection and Fine-Gra

IDEAL-Bench: Indoor Dataset and Evaluation suite for Analyzing 3D Layout reasoning

arXiv:2607.03614v1 Announce Type: new Abstract: Spatial question answering is the dominant paradigm for evaluating spatial intelligence in Vision-Language Models (VLMs), but it leaves a complementary

IndustryNav: Exploring Spatial Reasoning of Embodied Agents in Dynamic Industrial Navigation

arXiv:2511.17384v2 Announce Type: replace-cross Abstract: While Visual Large Language Models (VLLMs) show great promise as embodied agents, they continue to face substantial challenges in spatial reas

IRC-Bench: Recognizing Entities from Contextual Cues in First-Person Reminiscences

arXiv:2605.06142v2 Announce Type: replace-cross Abstract: When people recount personal memories, they often refer to people, places, and events indirectly, relying on con-textual cues rather than expl

iVISION-2DCD: A Long-Term Change Detection Dataset for Large-Scale Outdoor Construction Monitoring

arXiv:2607.03553v1 Announce Type: new Abstract: Automation in construction is essential for reducing costs and human errors in large-scale projects. We approach the construction progress monitoring fr

K9-Bench: Evaluating Multimodal LLMs on Canine-Centric Videos

arXiv:2607.02680v1 Announce Type: cross Abstract: MLLMs have shown strong zero-shot capabilities across diverse inputs such as across images, video, audio, and text. A crucial, yet underexplored, appl

Local Ai

Kairos: A Regret-Aware Native World-Action Model Stack for Physical AI

arXiv:2606.16533v3 Announce Type: replace Abstract: We introduce extbf{Kairos}, a regret-aware native world-action model stack for Physical AI. Kairos is motivated by the view that a physical world mo

local-aiarxiv-cs-ai

Knowing When to Stop: Predicting Execution-Consistency Convergence in Text-to-SQL

arXiv:2607.03991v1 Announce Type: cross Abstract: Repeated LLM calls are the standard way to estimate how trustworthy a Text-to-SQL result is: run the pipeline multiple times, judge each SQL execution

Agents

Latent Programming Horizons in Coding Agents

arXiv:2607.05188v1 Announce Type: new Abstract: A coding agent solving a software-engineering task spends dozens of steps reasoning, editing code, and running tests, yet little is known about what the

agentsarxiv-cs-lg

Leveraging Pathology Co-occurrence for Test-Time Adaptation in Chest X-Ray Diagnosis

arXiv:2607.03715v1 Announce Type: new Abstract: Medical imaging models often degrade when deployed at new clinical sites due to differences in imaging equipment, protocols, and patient populations. Te

researcharxiv-cs-cv

LRX-PINN: A Layer-Resolving XNet Physics-Informed Neural Network with Integrated Cauchy Activations for Convection-Dominated Problems

arXiv:2607.03682v1 Announce Type: cross Abstract: Convection-dominated convection-diffusion problems often develop thin layers, where the solution has sharp transition profiles and its derivatives are

researcharxiv-cs-lg

Local Ai

MambaLIE: Scene Light Intensity-Boosted Low-Light Image Enhancement with State Space Model

arXiv:2607.03013v1 Announce Type: cross Abstract: Images captured by consumer electronic devices, such as mobile phones and digital cameras, often suffer from low-light degradation due to sensor limit

local-aiarxiv-cs-ai

Measuring What Matters: A Unified Evaluation Framework for GNN Explainability

arXiv:2607.04600v1 Announce Type: new Abstract: Graph eXplainable AI (G-XAI) is increasingly important for making Graph Neural Networks interpretable and accountable. While a growing number of explain

researcharxiv-cs-lg

Local Ai

MetaSkill-Evolve: Recursive Self-Improvement of LLM Agents via Two-Timescale Meta-Skill Evolution

arXiv:2607.05297v1 Announce Type: new Abstract: Recent LLM agents tackle increasingly long-horizon, open-ended tasks, and external skills, reusable procedural knowledge supplied to the agent, further

local-aiarxiv-cs-ai

MMEarth-Bench: Global Model Adaptation via Multimodal Test-Time Training

arXiv:2602.06285v2 Announce Type: replace Abstract: Recent research in geospatial machine learning has demonstrated that models pretrained with self-supervised learning on Earth observation data can p

Naive PAINE: Lightweight Text-to-Image Generation Improvement with Prompt Evaluation

arXiv:2603.12506v2 Announce Type: replace-cross Abstract: Text-to-Image (T2I) generation is primarily driven by Diffusion Models (DM) which rely on random Gaussian noise. Thus, like playing the slots

researcharxiv-cs-ai

Natural Language Camera Movement Understanding

arXiv:2607.03043v1 Announce Type: new Abstract: Understanding camera movement in natural language is critical for training and evaluating video generation models, among other applications. However, we

NKI-Agent: Domain-Specific Fine-Tuning and Agentic Tool Use for Neuron Kernel Generation

model-releasesarxiv-cs-lg

arXiv:2607.04395v1 Announce Type: new Abstract: Recent agentic approaches to LLM-based kernel generation have achieved impressive results on CUDA. For emerging AI accelerators such as AWS Trainium and

OmniFocus: Query-Guided Modality-Balanced Token Compression for Omni-Modal Large Language Models

arXiv:2607.03050v1 Announce Type: cross Abstract: Omni modal large language models (OmniLLMs) have attracted wide attention for their ability to jointly process audio and video, but they generate larg

Open-Attribute Person Retrieval: Finding People Through Distinctive and Novel Attributes

arXiv:2508.01389v3 Announce Type: replace Abstract: Person retrieval in surveillance videos often depends on attributes described by witnesses or operators. However, the most useful cues in practice a

safetyarxiv-cs-cv

Polarity Detection of Sustainable Development Goals in News Text

arXiv:2509.19833v4 Announce Type: replace-cross Abstract: The United Nations' Sustainable Development Goals (SDGs) provide a globally recognised framework for addressing major societal, environmental,

Prior Bias in Vision Language Models on UML Diagram Interpretation

arXiv:2607.02853v1 Announce Type: new Abstract: Vision Language Models (VLMs) are increasingly applied to software engineering artifacts, especially UML class diagrams whose meaning depends on visual

Re:Form -- Reducing Human Annotations in Scalable Formal Software Verification with RL in LLMs: A Preliminary Study on Dafny

arXiv:2507.16331v4 Announce Type: replace Abstract: Existing informal language-based (e.g., human language) Large Language Models (LLMs) trained with Reinforcement Learning (RL) face a significant cha

RL Forgets! Towards Continual Policy Optimization

model-releasesarxiv-cs-lg

arXiv:2607.04364v1 Announce Type: new Abstract: Continual post-training is becoming a central paradigm for adapting vision-language models to evolving tasks. Recent work has increasingly favored reinf

RoboVista: Evaluating Vision Language Models for Diverse Robot Applications

model-releasesarxiv-cs-ro

arXiv:2607.04610v1 Announce Type: new Abstract: Diverse applications for robotics, such as industry and agriculture, require robots to operate across various embodiments, changing visual conditions, a

RSPO: Reward-Swap Policy Optimization for Multi-Turn LLM Agents

arXiv:2607.04713v1 Announce Type: cross Abstract: Reinforcement learning holds significant potential for training large language models (LLMs) to handle multi-turn interactive tasks. However, in long-

safetyarxiv-cs-ai

SAGE: Synchronized Action-Gaze Recognition and Anticipation for Human Behavior Understanding

arXiv:2607.04017v1 Announce Type: new Abstract: Human object interaction (HOI), gaze pattern, and their anticipation are intricately linked, providing valuable insights into cognitive processes, inten

Seduced by the Narrative: Assessing Rule Adherence in Semi-Open Textual Sandboxes

arXiv:2607.02802v1 Announce Type: cross Abstract: As LLMs are increasingly deployed as autonomous adjudicators in semi-open textual game environments, robust rule adherence becomes critical when user

Spectral Signatures of Large Language Models

arXiv:2607.03377v1 Announce Type: cross Abstract: The rapidly growing repository of publicly available large language models (LLMs) presents significant challenges for systematic management and quanti

Hardware

SPORK: Self-Speculative Forking to Accelerate Agentic LLM Inference

arXiv:2607.03333v1 Announce Type: cross Abstract: LLM agents are becoming a common interface for research, coding, and question answering, yet their Thought-Action-Observation loop is often serial: th

hardwarearxiv-cs-ai