Search: “benchmark”

CROSS: Cascaded Distillation and Dual-Constraint Grounding for Remote Sensing Referring Segmentation

arXiv:2608.03147v1 Announce Type: new Abstract: Referring Remote Sensing Image Segmentation (RRSIS) has achieved significant progress through the integration of VLMs and the Segment Anything Model (SA

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CrossScope: A Role-Asymmetric World Model for Joint Dual-Scope Surgical Video Prediction

DGX agent

arXiv:2608.03211v1 Announce Type: new Abstract: Visual world models typically learn future dynamics from a single observation stream, limiting their ability to model cooperative systems with multiple

model-releasesarxiv-cs-cv

5 Aug 2026

CUADebug: Diagnosing and Repairing Computer-Use Agent Failures

arXiv:2608.02643v1 Announce Type: cross Abstract: Computer-use agents (CUAs) operate real desktop and web interfaces through screenshots, mouse and keyboard actions, and stateful UI feedback, yet thei

CUDA MPC: A GPU-Native Solver for Model Predictive Control

model-releasesarxiv-cs-ro

arXiv:2608.03051v1 Announce Type: new Abstract: Model Predictive Control (MPC) delivers constraint-aware control, but its reliance on online optimization limits its use on systems with fast dynamics,

Applications

CURV: Enhancing Chart Understanding Through Curriculum Visual Grounded Reasoning

arXiv:2608.02833v1 Announce Type: cross Abstract: Chart question answering (CQA) requires multimodal large language models (MLLMs) to integrate visual comprehension with logical reasoning, yet current

applicationsarxiv-cs-ai

DAIF: A Data-Driven Intermediate Fusion Framework for Multimodal Supervised Learning via Approximate Message Passing

model-releasesarxiv-cs-lg

arXiv:2608.02769v1 Announce Type: cross Abstract: Multimodal supervised learning seeks to leverage multiple heterogeneous data sources to improve predictive performance. A central challenge is determi

Design Criteria for SGD Preconditioners: Local Conditioning, Noise Floors, and Basin Stability

arXiv:2511.19716v3 Announce Type: replace-cross Abstract: Stochastic Gradient Descent (SGD) often slows in the late stage of training due to anisotropic curvature and gradient noise. We analyze precon

researcharxiv-cs-lg

Distilled Roads: Generalisable Road Network Extraction Across Sensors, Resolutions, and Region

arXiv:2608.03407v1 Announce Type: cross Abstract: Road network segmentation from satellite imagery remains challenging due to large geographic variation in road appearance, occlusions, and domain shif

Diversity is Not Ambiguity: Toward Accurate and Efficient Ambiguity Detection for Open-Domain QA

arXiv:2608.03177v1 Announce Type: new Abstract: How can question answering (QA) systems determine whether a query is ambiguous? Ambiguity detection is essential in open-domain QA, as misclassification

DocTrace: Towards Traceable Long Document VQA via Hierarchical Evidence Graph Reasoning

arXiv:2608.03292v1 Announce Type: new Abstract: Long Document Visual Question Answering (LongDocVQA) requires Multimodal Large Language Models (MLLMs) to locate, integrate, and reason over heterogeneo

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Don't Peek at the Answer: Outcome-Masked Group Relative Policy Optimization for Label-Free RLVR

arXiv:2608.03119v1 Announce Type: new Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) improves LLM reasoning but typically relies on ground-truth (GT) answers, limiting scalability. Vo

safetyarxiv-cs-ai

Don't Walk the Line: Boundary Guidance for Filtered Generation

arXiv:2510.11834v3 Announce Type: replace-cross Abstract: Generative models are increasingly paired with safety classifiers that filter harmful or undesirable outputs. A common strategy is to fine-tun

DP-MemView: A Memory Interface for Attribute-Level Transcript Privacy in Long-Term LLM Agents

arXiv:2608.03130v1 Announce Type: cross Abstract: Long-term memory enables persistent personalization in LLM agents, but repeated memory-conditioned responses can cumulatively reveal protected attribu

DriftWorld: Fast World Modeling through Drifting

arXiv:2607.15065v2 Announce Type: replace-cross Abstract: Predictive world models enable robots to plan by imagining the outcomes of their actions, but their value for control hinges on generating man

safetyarxiv-cs-cv

Dynamically Allocating Evaluation Effort for Model Ranking

arXiv:2608.03437v1 Announce Type: new Abstract: While human evaluation is the gold standard in many NLP tasks, it suffers from prohibitive costs and poor scalability. When identifying top-performing m

Earth Embeddings

arXiv:2608.03410v1 Announce Type: new Abstract: Earth observation is moving from foundation models that users must run themselves toward embedding products that package model feature outputs as reusab

researcharxiv-cs-cv

Efficient Knowledge Distillation for LLMs: Offline Top-K Logits and a Fused Chunked KL Loss

arXiv:2608.03796v1 Announce Type: cross Abstract: Small language models are often the only option for deployment under tight latency, cost, and on-premises constraints, but they are rarely trained fro

Efficient Video Dataset Distillation via Cluster-Guided Prototype Blending

arXiv:2608.03269v1 Announce Type: cross Abstract: Video dataset distillation aims to compress a large video dataset into a compact surrogate set that preserves its training utility. Most existing appr

Enhancing Q-Value Updates in Deep Q-Learning via Successor-State Prediction

arXiv:2511.03836v2 Announce Type: replace Abstract: Deep Q-Networks (DQNs) estimate future returns by learning from transitions sampled from a replay buffer. However, the target updates in DQN often r

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Enhancing Tabular Learners with Context-Aware Semantic Embeddings

arXiv:2608.03565v1 Announce Type: new Abstract: While modern tabular learners excel at capturing statistical patterns, they frequently operate in a semantic vacuum, treating textual features as discre

Evaluating LLM Trade-offs for Enterprise Automation: Lessons from Workflow Generation in a Production Enterprise Platform

arXiv:2608.03311v1 Announce Type: cross Abstract: Enterprise compliance management requires rapid adaptation to evolving regulatory frameworks (e.g., DORA, AI RMF, FedRAMP) and tight remediation SLAs.

Evaluation Blindness: How Silent Measurement Failures Corrupt AI Systems from Training to Deployment

model-releasesarxiv-cs-lg

arXiv:2608.02786v1 Announce Type: new Abstract: AI systems can fail silently. The failure propagates through training loops, evaluation pipelines, and production monitoring stacks until downstream har

Exploiting Separability in Multi-Scale Grey-Box Bayesian Optimization

model-releasesarxiv-cs-lg

arXiv:2608.03045v1 Announce Type: new Abstract: We consider grey-box optimization problems where the decision variables naturally partition into black-box variables (as arguments to an expensive black

Externally Validated Breast Ultrasound Segmentation via Multi-task Learning with BI-RADS-Consistent Morphological Priors

arXiv:2511.15968v2 Announce Type: replace-cross Abstract: External validation of breast ultrasound segmentation models remains limited because internal train--test splits do not capture domain shifts

Failure-Informed Image Self-Augmentation for Multimodal Large Language Model Self-Improvement

arXiv:2608.03733v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) have achieved remarkable performance across vision-language tasks, but their progress depends heavily on large-

Agents

Field Aware Agent Skill Retrieval

arXiv:2608.02880v1 Announce Type: cross Abstract: As lifelong learning agents accumulate lifelong growing skill banks, retrieving the correct skill becomes an increasingly important bottleneck. Most c

agentsarxiv-cs-lg

FLARE: Few-shot Learning-based Adaptive Reflective Engine

arXiv:2608.02919v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed in complex, compound AI systems where performance hinges on the quality of prompts. Recent state-

FraQ: Efficient Coordinate-Space Recompression for Federated Low-Rank Adaptation

arXiv:2608.03605v1 Announce Type: new Abstract: Federated fine-tuning with Low-Rank Adaptation (LoRA) enables efficient collaborative adaptation of Large Language Models (LLMs) without centralizing pr

From Generator to Embedder: Harnessing Innate Abilities of Multimodal LLMs via Building Zero-Shot Discriminative Embedding Model

arXiv:2508.00955v3 Announce Type: replace-cross Abstract: Adapting generative Multimodal Large Language Models (MLLMs) into universal embedding models typically demands resource-intensive contrastive

From Social Coding to Agentic Coding: Productivity and Relational Reconfiguration in Open-Source Communities

arXiv:2608.03585v1 Announce Type: new Abstract: Open-source software communities are a form of digital public infrastructure that not only produces code, but also generates public knowledge and interp

GENESIS: Towards Explainable Causal Discovery

arXiv:2608.03868v1 Announce Type: cross Abstract: Causal Discovery (CD) from observational data faces two fundamental challenges. First, purely statistical methods often lack the power to resolve stru

Applications

GeoMAR: Unleashing Geometrically Aligned Features for Masked Autoregressive Blind Face Restoration

arXiv:2608.03923v1 Announce Type: new Abstract: Codebook-based blind face restoration (BFR) often suffers from ambiguous conditioning features and a fragile prediction mechanism under severe degradati

applicationsarxiv-cs-cv

Local Ai

GLOBE: Trajectory-Aligned Gradient Matching with Structured SparseOptimization for Coreset Selection

arXiv:2608.02690v1 Announce Type: new Abstract: On-device training of deep neural networks is fundamentally constrained by the computational and memory costs of large-scale datasets. Coreset selection

local-aiarxiv-cs-lg

GORDON: Graph-based Object-centric Rewards for Decomposition of Long-Horizon Manipulation

arXiv:2608.03753v1 Announce Type: new Abstract: Learning long-horizon manipulation skills with reinforcement learning remains challenging due to the complexity of reward design, the limited guidance o

safetyarxiv-cs-ro

GraphCliff: Short-Long Range Gating for Modeling Critical Activity Changes Caused by Subtle Molecular Differences

arXiv:2511.03170v3 Announce Type: replace-cross Abstract: The quantitative structure-activity relationship assumes a smooth mapping between molecular structure and biological activity. However, activi

GUI-Lens: Coarse-to-Fine Cropping for GUI Grounding with General-Purpose VLMs

arXiv:2608.03270v1 Announce Type: cross Abstract: GUI grounding maps natural-language instructions to click locations and is essential for reliable GUI agents. The task remains difficult on high-resol

Hey everyone! I just released a sub-6B sparse activation AI model which was built with a brand new architecture : fusion. I fused weights fr…

model-releasesemad-mostaque--x

Hey everyone! I just released a sub-6B sparse activation AI model which was built with a brand new architecture : fusion. I fused weights from @liquidai's LFM2.5-2.6B & @Alibaba_Qwen's Qwen3.6-35B-A3B

Hi-Token: Hierarchical Coordinate Tokenization for Generative Visual Grounding

arXiv:2608.03471v1 Announce Type: new Abstract: Generative Vision-Language Models (VLMs) commonly treat bounding-box coordinates as independent output symbols, leaving numerical order and axis semanti

safetyarxiv-cs-cv

HUKUKBERT: Domain-Specific Language Model for Turkish Law

arXiv:2604.04790v2 Announce Type: replace Abstract: Natural language processing (NLP) advances have powered a generation of LegalTech systems, but Turkish law remains under-served by domain-specific d

Hunyuan3D-Buffalo 1.0: A Unified Multimodal Model for Scalable 3D Generation, Understanding, and Editing

arXiv:2608.02711v1 Announce Type: new Abstract: Recent advances in image generation have demonstrated the potential of unified multimodal models that integrate understanding, generation, and editing.

researcharxiv-cs-cv

HyperFL: Query-Adaptive Representation Learning for Software Fault Localization

arXiv:2608.02967v1 Announce Type: cross Abstract: Software fault localization identifies the code locations responsible for reported issues and is a fundamental step toward automated debugging and pro

HyVIC: A Metric-Driven Spatio-Spectral Hyperspectral Image Compression Architecture Based on Variational Autoencoders

model-releasesarxiv-cs-cv

arXiv:2603.26468v2 Announce Type: replace Abstract: The rapid growth of hyperspectral data archives in remote sensing (RS) necessitates effective compression methods for storage and transmission. Rece

I remember a time when 'flash' meant 32B

model-releasesr-localllama

I mean, Deepseek V4 Flash is an absolutely fantastic model, even though I can't run it on my machine it's so fascinating to see how it performs. Knowing that potentially it could be run at home is rea

In-Context Collapse in Vision-Language Models and How to Mitigate it?

arXiv:2608.02830v1 Announce Type: cross Abstract: Many-shot in-context learning (ICL) lets vision-language models (VLMs) adapt from image--label demonstrations without weight updates, and is widely as

Intertemporal Preference Steering in Qwen3 via Contrastive Activation Addition

arXiv:2608.03892v1 Announce Type: new Abstract: We study linear representations of temporal horizon in the large language model Qwen3-32B and use them to change the model's time-related preferences, r

Agents

IR2Solve: Structured Intermediate Representations for Cost-Efficient Optimization Autoformulation

arXiv:2608.02641v1 Announce Type: cross Abstract: Large language models (LLMs) can translate natural-language optimization problems into solver-ready formulations, but direct code generation is brittl

agentsarxiv-cs-ai

Local Ai

Keep the Needle, Prune the Haystack: Defect-Preserving Token Pruning for Efficient Zero-Shot Anomaly Detection

arXiv:2608.03681v1 Announce Type: new Abstract: Zero-shot visual anomaly detection has achieved remarkable progress, with recent vision-only approaches further improving performance while simplifying

local-aiarxiv-cs-cv

Applications

Large language models for partial differential equation workflows

arXiv:2608.03600v1 Announce Type: new Abstract: Partial differential equations (PDEs) become actionable in science and engineering not as isolated formulae, but as executable workflows that connect mo

applicationsarxiv-cs-ai