Search: “benchmark”

PIPBench: A Profile-Inclusive Framework for Personalized Image Generation Evaluation

arXiv:2607.06440v1 Announce Type: new Abstract: Recent text-to-image models such as DALLE-3 excel at following diverse prompts yet remain blind to individual aesthetic preferences. We study personaliz

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Population-Level Profiling of DSM-5 Depressive Symptoms Among Self-Reported ADHD and ASD Users on Twitter: An Exploratory Study Using Advanced NLP and Statistical Analysis

DGX agent

arXiv:2607.05626v1 Announce Type: new Abstract: Background: Depression frequently co-occurs with ADHD and autism spectrum disorder (ASD), but population-level differences in symptom expression between

model-releasesarxiv-cs-cl

8 Jul 2026

Privilege and confidentiality in generative AI workflows

arXiv:2607.05479v1 Announce Type: cross Abstract: Generative AI (GenAI) systems store and process client data in three distinct ways: in the model's parameters through training and memorisation, in th

Progressive Reasoning with Primitive Correction for Compositional Zero-Shot Learning

arXiv:2607.05911v1 Announce Type: new Abstract: Compositional Zero-Shot Learning (CZSL) aims to combine known attributes and objects as primitives for recognizing previously unseen attribute-object pa

researcharxiv-cs-cv

Prompt-Adapter Context Routing for Parameter-Efficient Multi-Shot Long Video Extrapolation

arXiv:2607.06481v1 Announce Type: cross Abstract: We present PACR-Video, a parameter-efficient framework for multi-shot long video extrapolation that preserves recurring entities, scene structure, vis

Agents

Prompt-to-Paper: Agentic AI System for Bioinformatics

arXiv:2607.05456v1 Announce Type: new Abstract: While recent advances in large language models have enabled end-to-end automated manuscript generation, existing systems suffer from three critical defi

agentsarxiv-cs-ai

PVCap: Towards Accurate 3D Dense Captioning via PseudoCap and VoxelCapNet

arXiv:2607.06097v1 Announce Type: cross Abstract: 3D dense captioning, an emerging vision-language task, aims to generate descriptive sentences for each object in the 3D scene. Despite the impressive

researcharxiv-cs-ai

Rate of improvement is accelerating. Users should notice a meaningful improvement in the usefulness of the Grok Build harness with our V9 fo…

Rate of improvement is accelerating. Users should notice a meaningful improvement in the usefulness of the Grok Build harness with our V9 foundation model (aka Grok 4.5) every week. Grok 4.5. Pareto d

applicationselon-musk--x

Really excited to partner with @nvidia on the NemoClaw Deep Agents Blueprint Deep Agents is a fully open source agent harness that we are tu…

model-releasesharrison-chase--x

Really excited to partner with @nvidia on the NemoClaw Deep Agents Blueprint Deep Agents is a fully open source agent harness that we are tuning to make perform incredibly well with open models Introd

Replication in Visual Diffusion Models: A Survey and Outlook

arXiv:2408.00001v2 Announce Type: replace-cross Abstract: Visual diffusion models have revolutionized the field of creative AI, producing high-quality and diverse content. However, they inevitably mem

applicationsarxiv-cs-ai

RFHNet: Relational and Frequency-Aware Hashing Network for Large-Scale Fine-Grained Food Image Retrieval

arXiv:2607.06148v1 Announce Type: new Abstract: Fine-grained food image retrieval is a key task in computational gastronomy, with applications in food traceability, dietary monitoring, and smart cater

RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models

arXiv:2607.06504v1 Announce Type: new Abstract: Recent years have witnessed the emergence of multivariate modeling using time series foundation models (TSFMs), which achieve advanced zero-shot general

applicationsarxiv-cs-ai

SAGE: Spatial-visual Adaptive Graph Exploration for Efficient Visual Place Recognition

arXiv:2509.25723v4 Announce Type: replace Abstract: Visual Place Recognition (VPR) requires robust retrieval of geotagged images despite large appearance, viewpoint, and environmental variation. Prior

Scene Graph Thinking: Reinforcing Structured Visual Reasoning for Multimodal Large Language Models

arXiv:2607.05716v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have demonstrated strong perception and reasoning capabilities. However, most existing models focus on isolated

researcharxiv-cs-cv

SearchEyes: Towards Frontier Multimodal Deep Search Intelligence via Search World Simulation

arXiv:2607.05943v1 Announce Type: new Abstract: Training multimodal search agents to perform multi-hop reasoning remains challenging due to a fundamental structural disconnect: existing pipelines cons

safetyarxiv-cs-ai

Segmentation before Answering: Pixel Grounding for MLLM Visual Reasoning

arXiv:2607.05798v1 Announce Type: cross Abstract: Recent advancements in Multimodal Large Language Models (MLLMs) have evolved from static perception to interleaved visual-language reasoning, often re

researcharxiv-cs-ai

Self-Review Reinforcement Learning (SRRL) with Cross-Episode Memory and Policy Distillation

arXiv:2607.05541v1 Announce Type: cross Abstract: Reinforcement Learning is commonly used to train large language models using environmental feedback. In applied settings, the environment usually prov

SIEVE: Structure-Aware Data Selection for Imitation Learning with VLA Models

arXiv:2607.06442v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models are typically trained by imitation learning on large-scale robot demonstration datasets, but more data does not nece

researcharxiv-cs-ro

Social 3D Scene Graphs: Modeling Human Actions and Relations for Interactive Service Robots

arXiv:2509.24966v2 Announce Type: replace Abstract: Understanding how people interact with their surroundings and each other is essential for enabling robots to act in socially compliant and context-a

SpanUQ: Span-Level Uncertainty Quantification for Large Language Model Generation

model-releasesarxiv-cs-cl

arXiv:2607.05721v1 Announce Type: new Abstract: Uncertainty estimation is essential not only for the trustworthy deployment of large language models (LLMs) but also as a foundation for self-refinement

SpecTrack: Spectral Prompt Guided Adaptive Experts for Multispectral Object Tracking

arXiv:2607.05988v1 Announce Type: new Abstract: Multispectral image(MSI) and hyperspectral image(HSI) object tracking object tracking exploits recorded band-wise observations to improve target--backgr

researcharxiv-cs-cv

Straight-Path Flow Matching for Incomplete Multi-View Clustering

arXiv:2607.06281v1 Announce Type: new Abstract: Incomplete Multi-View Clustering addresses the problem of clustering multi-modal data when certain views are missing. Recent end-to-end generative appro

safetyarxiv-cs-cv

Structured-Condensed Prompt Tuning in Vision-Language Models for Fine-grained Image Recognition

arXiv:2607.06185v1 Announce Type: new Abstract: Fine-grained image recognition poses a significant challenge due to the substantial expertise and effort required for manual annotation. Vision-language

safetyarxiv-cs-cv

Superman: Unifying Skeleton and Vision for Human Motion Perception and Generation

arXiv:2602.02401v2 Announce Type: replace Abstract: Human motion analysis tasks, such as temporal 3D pose estimation, motion prediction, and motion in-betweening, play an essential role in computer vi

safetyarxiv-cs-cv

Supervised Reward Inference

model-releasesarxiv-cs-lg

arXiv:2502.18447v2 Announce Type: replace Abstract: Existing approaches to reward inference typically assume that humans provide demonstrations according to specific behavior models. However, humans o

The Balkanization of Execution-Security Research for AI Coding Agents: Isolation, Access Control, and Time-of-Check-to-Time-of-Use Vulnerabilities

arXiv:2607.05743v1 Announce Type: cross Abstract: AI coding agents now read repositories, call tools, and execute shell commands with limited human oversight, and a fast-growing body of work studies w

The Granularity Paradox: How Temporal Disaggregation Inflates In-Sample Fit and Compounds Out-of-Sample Error

arXiv:2607.05450v1 Announce Type: cross Abstract: This paper explores the 'Granularity Paradox' in time-series forecasting, wherein finer temporal disaggregation (e.g., Monthly to Weekly/Daily) improv

The relationship between reasoning and performance in large language models--o3 (mini) thinks harder, not longer

arXiv:2502.15631v2 Announce Type: replace-cross Abstract: Large language models have demonstrated remarkable progress in mathematical reasoning, leveraging chain-of-thought and reinforcement learning.

To Retain or to Adapt? Generalizing Continual Learning

arXiv:2607.05609v1 Announce Type: cross Abstract: The Continual Learning (CL) literature has long been driven by the goal of mitigating catastrophic forgetting. This objective rests on a pervasive, of

safetyarxiv-cs-ai

Agents

TRIG: Trajectory-Rig Decoupled Metric Geometry Learning

arXiv:2607.05801v1 Announce Type: new Abstract: Vision-centric autonomous driving requires accurate metric geometry and ego-motion estimation from synchronized multi-camera observations. Recent visual

agentsarxiv-cs-cv

UniLM-Nav: A Unified Framework for Zero-Shot Last-Mile Navigation

model-releasesarxiv-cs-ro

arXiv:2607.06537v1 Announce Type: new Abstract: Mobile manipulation requires a robot to navigate to a target object or receptacle and then perform intended manipulation. However, reaching the vicinity

Universal Algorithm-Implicit Learning

arXiv:2602.14761v2 Announce Type: replace-cross Abstract: Current meta-learning methods are constrained to narrow task distributions with fixed feature and label spaces, limiting applicability. Moreov

researcharxiv-cs-ai

Verification of Dynamic Holographic Behavior in Identity Documents

arXiv:2607.06466v1 Announce Type: new Abstract: This paper addresses the remote verification of the authenticity of Optically Variable Devices (commonly known as holograms) on identity documents. Typi

We need AI model selection to be MUCH easier ASAP. I want proactive flags from my AI systems suggesting models. I want my AI harness to say …

model-releasesallie-k--miller--x

We need AI model selection to be MUCH easier ASAP. I want proactive flags from my AI systems suggesting models. I want my AI harness to say 'hey allie, my girl, you keep asking for bar recommendations

What's new at IBM Quantum Q2 2026

IBM Quantum's Q2 2026 updates likely showcase advancements in quantum computing hardware, software, or services, including new processor capabilities, improved error correction, expanded cloud access,

researchibm-research

Tutorials

WING: A Window-Prior-Based Generative Network with Gated Inception for Cross-Modality CT Synthesis

arXiv:2607.06234v1 Announce Type: new Abstract: Generating CT volumes from MRI and CBCT can improve treatment planning in adaptive radiotherapy while avoiding additional radiation exposure. However, d

tutorialsarxiv-cs-cv

x-Prediction Is All You Need:Training-Free Accelerated Generation via Endpoint Decodability

arXiv:2607.06114v1 Announce Type: cross Abstract: Diffusion and flow matching models generate high-quality samples, but their ODE samplers often need tens to hundreds of neural function evaluations (N

A Large-Scale Dataset and a New Method for RemoteSensing Traffic Object Segmentation

arXiv:2607.03945v1 Announce Type: new Abstract: Remote sensing imagery plays a crucial role in evaluating regional transportation capacity. However, existing segmentation datasets often lack diversity

A Policy Decomposition Framework for Dynamic Order Fulfillment Operations

arXiv:2607.04056v1 Announce Type: cross Abstract: Modern supply chains span diverse operational environments, ranging from e-commerce distribution networks to customized production-to-order manufactur

safetyarxiv-cs-lg

A Reliable Context-Aware and Temporal Planning Framework for Autonomous Driving

arXiv:2607.04689v1 Announce Type: cross Abstract: Safe operation of autonomous vehicles in dense urban traffic depends on perception and planning that remain reliable when onboard sensing is degraded.

A Step Towards Robust Unsupervised Domain Adaptation via Fine-Tuning and Reinforcement Learning

arXiv:2607.03600v1 Announce Type: cross Abstract: Adversarial robustness in Unsupervised Domain Adaptation (UDA) remains a significant challenge due to noisy pseudo labels and inherent distributional

A Systematic Survey on Large Language Models for Evolutionary Optimization: From Modeling to Solving

arXiv:2509.08269v5 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly integrated with evolutionary computation to support optimization tasks. This survey primarily fo

A Technical Survey of Reinforcement Learning Techniques for Large Language Models

arXiv:2507.04136v2 Announce Type: replace Abstract: This survey offers a comprehensive foundation on the integration of RL with language models, highlighting prominent algorithms such as Proximal Poli

ACPO: Adaptive Credit Policy Optimization via Fine-Grained Surrogate Entropy

arXiv:2607.03126v1 Announce Type: cross Abstract: Reinforcement Learning (RL) has substantially improved the reasoning ability of large language models (LLMs), but sparse outcome rewards still make to

safetyarxiv-cs-ai

Advances in Neural Controlled Differential Equations

arXiv:2607.05280v1 Announce Type: new Abstract: Many real-world systems evolve continuously, yet most machine learning models interpret time series as discrete sequences. Continuous-time approaches in

applicationsarxiv-cs-lg

Adversarial LassoNet: Robust Feature Selection via Stability-Driven Sparse Learning

model-releasesarxiv-cs-lg

arXiv:2607.03839v1 Announce Type: new Abstract: Sparse feature selection is critical for high-dimensional machine learning, yet traditional ell_1-regularized methods are often brittle under observatio

Agent-driven Long-tail Simulation for Autonomous Driving

arXiv:2607.04331v1 Announce Type: cross Abstract: Evaluating autonomous driving systems in closed-loop settings requires realistic and interactive simulation, yet existing simulators largely rely on l

Local Ai

Agent Reinforcement Learning via Pivotal-Aware Self-Feedback Retry

arXiv:2607.03702v1 Announce Type: new Abstract: Large language model (LLM) agents have shown strong decision-making capabilities in long-horizon interactive tasks, yet they still struggle to effective

local-aiarxiv-cs-ai