Search: “models”

Learning Explicit Physical Parameter Control and Benchmarking for Video Generation

arXiv:2607.18924v1 Announce Type: new Abstract: Recent advances in image-to-video generation have improved visual realism, making physically grounded and controllable dynamics an important step toward

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MoAKE: Toward Unified All-in-One Action Quality Assessment via Mixture of Action Knowledge Experts

DGX agent

arXiv:2607.19826v1 Announce Type: new Abstract: Action Quality Assessment (AQA) aims to objectively evaluate performance quality from action videos. Most existing methods follow a ``one-by-one'' parad

applicationsarxiv-cs-cv

23 Jul 2026

Local Ai

MoGe-3: Fine-Detail Monocular Geometry Estimation with Self-Guided Sparse Volumetric Refinement

arXiv:2607.17967v2 Announce Type: replace Abstract: Monocular geometry estimation has recently achieved impressive performance across diverse scenes. However, state-of-the-art models still face notabl

local-aiarxiv-cs-cv

No Training, Better Flights: Test-Time Scaled VLMs for UAV Navigation

arXiv:2607.19288v1 Announce Type: new Abstract: Test-time scaling offers a promising method to improve the inference performance of Vision-Language Models (VLMs) without additional training. Existing

safetyarxiv-cs-cv

Pathologist Attention-Aligned Report Generation for Prostate Histopathology

arXiv:2607.19624v1 Announce Type: new Abstract: The allocation of visual attention by pathologists during cancer diagnosis is a highly selective process that critically shapes the information extracte

safetyarxiv-cs-cv

PathReportEval: A Systematic Benchmark for Pathology Report Generation

arXiv:2607.18448v1 Announce Type: cross Abstract: Pathology report generation from whole-slide images (WSIs) is a rapidly growing multimodal learning problem, yet progress is difficult to measure beca

PerfAgent: Profiler-Guided Iterative Refinement for Repository-Level Code Optimization

arXiv:2607.19653v1 Announce Type: cross Abstract: Large language model (LLM) agents now perform well on correctness-oriented repository-level tasks, including SWE-Bench issue resolution and feature im

PRiSM: Prototype Regularization for Few-Shot VLMs

arXiv:2607.17820v2 Announce Type: replace Abstract: Training-free few-shot adaptation methods have gained significant attention recently in the context of Vision-language Models (VLMs). Yet, current b

Prober.ai: Gated Inquiry-Based Feedback via LLM-Constrained Personas for Argumentative Writing Development

arXiv:2605.05598v2 Announce Type: replace Abstract: The proliferation of large language models (LLMs) in educational settings has paradoxically undermined the cognitive processes they purport to suppo

Reward-Aware Population Scaling of Evolutionary Strategies in LLM Fine-Tuning

arXiv:2607.19408v1 Announce Type: new Abstract: Using Evolutionary Strategies (ES) for fine-tuning large language models is attractive because it is memory-efficient, parallel, and compatible with bla

researcharxiv-cs-lg

Single-Teacher View Augmentation: Enhancing Knowledge Distillation with Student-Guided Perturbations

arXiv:2607.11557v2 Announce Type: replace Abstract: Knowledge distillation (KD) typically relies on the fixed perspective of a single teacher, limiting the diversity of supervisory signals. While mult

Sophisticated Policies from Epistemic Priors

arXiv:2607.19518v1 Announce Type: new Abstract: Sophisticated Inference is a variant of active inference often associated with recursive belief modeling and tree search. We argue that its central comp

Statistical Inference for Rank Allocation in Low-Rank Adaptation

model-releasesarxiv-cs-lg

arXiv:2607.20205v1 Announce Type: cross Abstract: Low-rank adaptation (LoRA) has become a widely used parameter-efficient fine-tuning method for large language models. Since different modules and laye

Unlearning as Distribution Restoration: A Controlled Counterfactual Study, a Validated Selective Screen, and the Limits of Oracle-Free Certification

arXiv:2607.19442v1 Announce Type: cross Abstract: Machine unlearning is commonly evaluated by matching a retrained oracle on trained probes. In a controlled nonce-fact testbed with a matched retrainin

Which Values Do LLMs Confuse? A Schwartz-Based Recognition Study

arXiv:2607.20270v1 Announce Type: new Abstract: Large language models are increasingly evaluated through the values they endorse, but such evaluations presuppose that models can identify the value exp

safetyarxiv-cs-cl

CAVA: Canonical Action Verification and Attestation for Runtime Governance of Agentic AI Systems

arXiv:2607.13716v1 Announce Type: new Abstract: Agentic AI systems increasingly act through heterogeneous runtimes: local coding hooks, SDK tools, browser automation, managed-agent traces, API gateway

CoDiffGRN: Rethinking Gene Regulatory Network Inference via the BEELINE-KGC Benchmark and Co-evolutionary Discrete Diffusion

arXiv:2607.13120v1 Announce Type: cross Abstract: Inferring gene regulatory networks (GRNs) from single-cell transcriptomic data is crucial for biological discovery, yet existing approaches suffer fro

Local Ai

Federated Explainable Artificial Intelligence: Roles, Architectures, Evaluation, and Open Challenges

arXiv:2607.13045v1 Announce Type: cross Abstract: Federated Learning (FL) has emerged as a key paradigm for privacy-preserving collaborative model training across distributed and heterogeneous data so

local-aiarxiv-cs-ai

From Prediction to Collaboration: Interactive Symbolic Music Analysis

arXiv:2607.13587v1 Announce Type: cross Abstract: Automatic symbolic music analysis has made substantial progress, yet existing systems are typically designed for a single mode of use, such as full-sc

How Far Can Root Cause Analysis Go on Real-World Telemetry Data?

arXiv:2607.13548v1 Announce Type: new Abstract: Identifying root causes in production microservice failures requires reasoning over large-scale, multimodal telemetry spanning metrics, logs, and traces

Applications

Multi-view Hand Reconstruction with a Point-Embedded Transformer

arXiv:2408.10581v3 Announce Type: replace Abstract: This work introduces a novel and generalizable multi-view Hand Mesh Reconstruction (HMR) model, named POEM, designed for practical use in real-world

applicationsarxiv-cs-cv

Peak-End-Net: A Peak-End Rule Inspired Framework for Generalizable Video Aesthetic Assessment

arXiv:2607.13941v1 Announce Type: new Abstract: Video aesthetic assessment (VAA) aims to predict how aesthetically pleasing a video is, yet remains far less explored than other visual assessment tasks

RAGthoven at SemEval-2026 Task 1: A Multi-Stage Pipeline Walks Into a Benchmark and Barely Clears the Bar

arXiv:2607.13189v1 Announce Type: cross Abstract: We present RAGthoven, our system for SemEval-2026 Task 1 (MWAHAHA), Subtask A (multilingual constrained humor generation in English, Spanish, and Chin

Safe Overtaking for Autonomous Racing Using Hierarchical Optimization and Learning-Based Control

model-releasesarxiv-cs-ro

arXiv:2607.13348v1 Announce Type: new Abstract: Autonomous racing overtaking requires balancing competitive performance with safety under nonlinear vehicle dynamics and real-time constraints. Model Pr

ScanFocus: A Coarse-to-Fine Framework for Spatio-Temporal Video Grounding

arXiv:2607.13421v1 Announce Type: cross Abstract: Spatio-Temporal Video Grounding (STVG) aims to retrieve the visual trajectory of a specific object from a video stream as described by a natural langu

Applications

Semantic Anchoring for Robotic Action Representations

arXiv:2607.13597v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models inherit rich semantic representations from pretrained Vision-Language Models, yet fine-tuning on limited robot dem

applicationsarxiv-cs-ai

Targeted Recovery of Weight-Space Mechanisms From Neural Networks

model-releasesarxiv-cs-lg

arXiv:2607.13047v1 Announce Type: new Abstract: Parameter decomposition (PD) decomposes neural networks into interpretable computational components that faithfully reflect the original network's opera

TheBioCollection: Unified Pre-Training Scale LLM Corpus for Biology

arXiv:2607.08803v2 Announce Type: replace-cross Abstract: The push toward large language models for biology (BioLM) has created a need for training corpora that can endow models with a genuine underst

researcharxiv-cs-ai

Agents

Too Polite to Disagree: Understanding Sycophancy Propagation in Multi-Agent Systems

arXiv:2604.02668v2 Announce Type: replace-cross Abstract: Large language models (LLMs) often exhibit sycophancy: agreement with user stance even when it conflicts with the model's opinion. While prior

agentsarxiv-cs-ai

VGIF-Score: Interpretable and Diagnostic Evaluation of Spatio-Temporal Instruction Following in Video Generation

arXiv:2607.13527v1 Announce Type: new Abstract: Recent video generation models (VGMs) have made substantial progress in visual fidelity, yet their ability to follow long, compositional instructions re

When Agents Disagree With Themselves: Behavioral Consistency as an Uncertainty Signal for LLM Agents

arXiv:2602.11619v2 Announce Type: replace Abstract: Running the same LLM agent on identical inputs yields 2.3-4.2 distinct action sequences per 10 runs; this behavioral variance constitutes a training

A Shortcut to Statistically Steady-State Turbulence with Flow Matching

arXiv:2607.13022v1 Announce Type: cross Abstract: Many nonlinear physical systems exhibit an initial transient phase in which perturbations grow before nonlinear interactions lead to a statistically s

researcharxiv-cs-lg

ACID: Adaptive Caching for vIDeo generation

arXiv:2607.12358v1 Announce Type: new Abstract: Video diffusion models produce high-quality generations but remain slow at inference due to their sequential denoising procedure. Caching-based accelera

Adaptive Cross-Modal Fusion with Sparse Attention for Pedestrian Crossing Intention Prediction

arXiv:2607.12293v1 Announce Type: new Abstract: Predicting pedestrian crossing intention is a safety-critical task for autonomous driving, yet existing approaches often rely on single-modal inputs or

Adversarial Attacks on Online Handwriting using Salience-based Temporal Editing

arXiv:2607.12500v1 Announce Type: cross Abstract: Deep learning models for online handwriting recognition have been shown effective and are increasingly deployed in practical applications. However, th

Applications

An Empirical Analysis of Continual Learning for Heterogeneous Medical Visual Question Answering

arXiv:2607.12048v1 Announce Type: cross Abstract: Deploying medical visual question answering (MedVQA) systems in real-world clinical settings requires models that adapt to new clinical tasks without

applicationsarxiv-cs-ai

Bringing Back Rule Induction to Fluid Intelligence Research? An Initial Validation of the ARC-AGI Benchmark in Humans

arXiv:2607.11263v2 Announce Type: replace Abstract: Two competing perspectives on fluid intelligence (gf) measures propose that performance is primarily constrained either by working memory capacity o

Deployable Human Preference Alignment in Robotics: Learning Representative Rewards from Diverse Human Preferences

arXiv:2607.12466v1 Announce Type: new Abstract: Aligning robot policies with human preferences is essential for deployment to diverse end users. In per-user alignment approach, preference feedback is

safetyarxiv-cs-ro

Domain-Incremental Remote Sensing Change Detection via Difference-Guided Adaptation and Frequency-Decoupled Distillation

arXiv:2607.12934v1 Announce Type: new Abstract: Remote sensing change detection (RSCD) models are prone to catastrophic forgetting when incrementally adapted to new domains. Existing domain-incrementa

Edge-Aware Thermal Infrared UAV Swarm Tracking

arXiv:2607.12544v1 Announce Type: new Abstract: Thermal infrared (TIR) imaging is essential for UAV swarm operations in visually degraded environments. However, tracking tiny UAVs remains challenging

FairCoder: Probing LLM Bias in High-Stakes Decision Making via Coding Tasks

model-releasesarxiv-cs-cl

arXiv:2501.05396v3 Announce Type: replace Abstract: Large language models (LLMs) are increasingly used in high-stakes decisions such as hiring and college admissions, making their social bias a critic

Local Ai

Follow the Latent Roadmap: Navigating Revocable Decoding for Diffusion LLMs with Anchor Tokens

arXiv:2606.16847v3 Announce Type: replace-cross Abstract: Diffusion Large Language Models (dLLMs) offer a promising avenue for parallel generation but face a trade-off between decoding speed and quali

local-aiarxiv-cs-ai

From Critic to Confidence: PPO for Language-Based Quantitative Prediction with Confidence Estimation

arXiv:2607.12687v1 Announce Type: cross Abstract: LLMs can perform language-based quantitative prediction from unstructured inputs, but remain susceptible to hallucinations and overconfident errors, m

Generalization and Memorization in Rectified Flow

arXiv:2603.13421v2 Announce Type: replace-cross Abstract: Generative models based on the Flow Matching objective, particularly Rectified Flow, have emerged as a dominant paradigm for efficient, high-f

Tutorials

Invariant Learning Dynamics of Transformers in Inductive Reasoning Tasks

arXiv:2607.11875v2 Announce Type: replace-cross Abstract: We present a theoretical framework to explain the emergence of inductive reasoning abilities in Transformer language models. While previous wo

tutorialsarxiv-cs-ai

KnowAct-GUIClaw: Know Deeply, Act Perfectly, Personal GUI Assistant with Self-Evolving Memory and Skill

model-releasesarxiv-cs-cl

arXiv:2607.12625v1 Announce Type: new Abstract: OpenClaw has emerged as a leading agent framework for complex task automation, yet it faces insufficient cross-platform GUI interaction support and a we

LatentFlow: A General Framework for Conditioning Stochastic Processes

arXiv:2607.12922v1 Announce Type: cross Abstract: Stochastic-process models are, as a rule, far easier to simulate than to condition. Non-linear observations, non-Gaussian likelihoods, black-box infor

researcharxiv-cs-lg

LiteTopK: Exploiting the Curse of Dimensionality for a Fused Indexer-TopK Kernel in Long-Context Sparse Attention

model-releasesarxiv-cs-lg

arXiv:2607.11976v1 Announce Type: new Abstract: Indexer-TopK, the operation to compute the scores and select the top-k candidates, is widely used by sparse attention kernels in large language models a