Search: “benchmark”

Spike-based Belief Propagation in Nonlinear Dynamical Systems

arXiv:2608.19907v1 Announce Type: new Abstract: This paper presents a Bayesian control framework that integrates spike-based dynamics with probabilistic inference for adaptive control. Bayesian infere

Local Ai

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SPyCE: Skill-Policy Co-evolution for Multimodal Agents

DGX agent

arXiv:2607.13854v2 Announce Type: replace Abstract: Multimodal agents that think with images iteratively manipulate visual evidence and invoke tools across many steps. Existing reinforcement learning

local-aiarxiv-cs-cl

21 Aug 2026

SWE-bench Science: Can Coding Agents Resolve Engineering Tasks in Science?

arXiv:2608.19799v1 Announce Type: new Abstract: Software increasingly functions as part of the scientific instrument itself, making failures in scientific code capable of compromising not only program

Applications

TESTNAV: Pareto-Guided Search for Compositional Robustness Testing

arXiv:2608.19882v1 Announce Type: new Abstract: Deep learning models remain vulnerable to real-world input perturbations, especially when multiple corruptions co-occur in the same input (e.g., brightn

applicationsarxiv-cs-ai

The impact of feature engineering and an optimisation framework for ocean colour machine learning

model-releasesarxiv-cs-lg

arXiv:2608.19899v1 Announce Type: cross Abstract: Machine learning (ML) is widely used for the development of ocean colour algorithms, but most studies focus on model parameter training and hyperparam

Ultra-High-Definition Restoration Transformers with Correlation Matching Transformation

arXiv:2608.20263v1 Announce Type: new Abstract: We propose UHDformer++, a general Transformer-based framework to solve numerous Ultra-High-Definition (UHD) image restoration tasks. UHDformer++ operate

VGI-BENCH: Probing Visual Intelligence in Video Generation Models

arXiv:2608.19583v1 Announce Type: cross Abstract: Recent studies suggest that video generation models can exhibit certain forms of zero-shot visual reasoning through generated frames. Yet reliable eva

researcharxiv-cs-ai

Video Evidence to Reasoning Efficient Video Understanding via Explicit Evidence Grounding

arXiv:2601.07761v2 Announce Type: replace Abstract: Large Vision-Language Models (LVLMs) face a fundamental dilemma in video reasoning: they are caught between the prohibitive computational costs of v

safetyarxiv-cs-cv

What Matters for Latent Actions in Robot Learning

arXiv:2608.19613v1 Announce Type: cross Abstract: Latent Action Models (LAMs) have emerged as a promising paradigm for enabling robot learning to leverage large-scale unlabeled videos through latent a

safetyarxiv-cs-cv

When Automata Meet Streams: Temporal Logic Compilation for Stream-Based Robotics Task and Motion Planning

arXiv:2608.19453v1 Announce Type: new Abstract: Stream-based robotics Task and Motion Planning (TAMP) integrates discrete symbolic planning with dynamically generated continuous geometric parameters,

safetyarxiv-cs-ro

When Contextual Inference Fails: Cancelability in Interactive Instruction Following

arXiv:2603.19997v2 Announce Type: replace Abstract: We investigate the separation of literal interpretation from contextual inference in a collaborative block-building tasks, where an agent must resol

When Irrelevant Text Matters: Affine Margin Shifts in Multimodal Large Language Models

arXiv:2608.19208v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) are frequently exposed to auxiliary textual context, the impact of which on visually grounded tasks remains und

safetyarxiv-cs-cl

When Text and Numbers Disagree: Evidence Arbitration in Large Language Models

arXiv:2608.20116v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used in settings where textual summaries, numerical observations, and external tool outputs may provide co

WithEveryone: Unified Planning and Identity Grounding for Group Image Generation

arXiv:2608.20336v1 Announce Type: new Abstract: Identity-preserving image generation becomes increasingly unreliable when a scene must contain many specified people. Beyond retaining each identity, th

World-Model-Grounded LLM Planning for AUV and ASV Navigation Near Offshore Wind Farms

model-releasesarxiv-cs-ro

arXiv:2608.19661v1 Announce Type: new Abstract: Large language models can turn a natural-language mission into a sequence of robot actions, but they do not have a sense of physics: they cannot judge h

Local Ai

Write Once, Run Everywhere: The Axon DSL for Shape-Safe and Framework-Agnostic LLM Architectures

arXiv:2608.19889v1 Announce Type: new Abstract: The entire ecosystem of open-source language models effectively relies on a single platform. What if this platform was forced to shut down tomorrow? Imp

local-aiarxiv-cs-ai

YolovN-CBi: A Lightweight and Efficient Architecture for Real-Time Detection of Small UAVs

arXiv:2512.18046v2 Announce Type: replace Abstract: Unmanned Aerial Vehicles, commonly known as, drones pose increasing risks in civilian and defense settings, demanding accurate and real-time drone d

A Critical Synthesis of Uncertainty Quantification and Foundation Models for Semantic Segmentation

arXiv:2608.18709v1 Announce Type: cross Abstract: Foundation models are increasingly breaking what seemed to be impossible not long ago by enabling unprecedented accuracy and cross-domain generalizati

A Framework and Prototype for a Navigable Map of Datasets in Engineering Design and Systems Engineering

arXiv:2603.15722v3 Announce Type: replace-cross Abstract: The proliferation of data across the system lifecycle presents both a significant opportunity and a challenge for Engineering Design and Syste

Atrial Fibrillation Detection with Arbitrary Leads via a Codebook-Based Reconstruction-Classification Framework

model-releasesarxiv-cs-lg

arXiv:2608.18451v1 Announce Type: new Abstract: extbf{Background and Objective}: Reliable atrial fibrillation (AF) detection from electrocardiogram (ECG) signals remains challenging in real-world clin

Budget-First Tariff Recommendation (BFTR): A Complete Algorithmic Framework for Telecom Plan Recommendation without Overcharging

arXiv:2608.18723v1 Announce Type: cross Abstract: Telecom operators traditionally offer predefined tariff grids, forcing users to choose from a limited set of plans. This paper proposes BFTR (Budget-F

CamWorldQA: Perceptual Quality Assessment of Camera-Controlled World Video Generation

arXiv:2608.18710v1 Announce Type: new Abstract: Recent advances in generative video models have enabled camera-controlled world video generation, allowing models to synthesize videos under user-define

Competence, Not Accuracy: A Diagnostic for Reference-Free Judge Gates in Skill Optimization

arXiv:2608.18719v1 Announce Type: new Abstract: Text-space skill optimization adapts a frozen agent by evolving a natural-language skill document, accepting each candidate through a validation gate. E

Compress and Forget: bitsandbytes Quantization Amplifies Proactive Interference in LLMs

arXiv:2608.18578v1 Announce Type: new Abstract: Proactive interference (PI) is a documented failure mode in large language models in which retrieval of a repeatedly overwritten value degrades as prior

COSTA: A Cluster-Centric Paradigm for Annotation-Free Open-Set Semantic Segmentation of Aerial Point Clouds with Domain Shifts

arXiv:2608.18479v1 Announce Type: new Abstract: Semantic segmentation of aerial point cloud is trapped in a generalization crisis under distinct domain shifts. While test-time adaptation offers a priv

researcharxiv-cs-cv

CTIFoundry: An Agent-Native Corpus Scaffold for Cyber Threat Intelligence

arXiv:2608.18613v1 Announce Type: new Abstract: Cyber threat intelligence (CTI) is increasingly consumed not by human analysts but by LLM agents that compose multi-step investigations at query time. T

DART-SD: Diamond-topology Aware Retrieval and Tuning for Self-Distillation of Multi-Turn Tool-Calling Agents

arXiv:2608.18524v1 Announce Type: cross Abstract: Equipping Large Language Models (LLMs) with multi-turn tool-calling capabilities is essential for building autonomous agents. However, progress is fun

safetyarxiv-cs-ai

DeepWeaver: Bridging the Evidence Synthesis Gap in Open-Ended Question Answering

arXiv:2608.18988v1 Announce Type: cross Abstract: Retrieve-then-generate pipelines are commonly used to produce deep-research answers for open-ended questions, but retrieval alone is insufficient: LLM

Agents

DentAgent: Evidence-Centric Multi-Agent Coordination for Multimodal Dental Reasoning

arXiv:2608.18878v1 Announce Type: new Abstract: Oral diseases affect billions of people worldwide, underscoring a pressing need for accurate and reliable dental assessment that integrates heterogeneou

agentsarxiv-cs-ai

Applications

Discretizing Continuous Time Series for Imputation with Masked Diffusion Training

arXiv:2608.19119v1 Announce Type: cross Abstract: Time series imputation is a crucial area for reliable time series analysis, yet it remains challenging due to the complex temporal dynamics and noise

applicationsarxiv-cs-ai

Agents

DocClaw: A Unified Agentic System for Intelligent Document Processing

arXiv:2608.18685v1 Announce Type: new Abstract: Intelligent document processing (IDP) encompasses a broad range of tasks, including optical character recognition (OCR), document question answering (Do

agentsarxiv-cs-cv

Agents

Dynamic SpectraFormer for Ultra-High-Definition Underwater Image Enhancement

arXiv:2608.18662v1 Announce Type: new Abstract: Underwater images suffer from color distortion, haze, and poor visibility due to light refraction and absorption in water. These challenges significantl

agentsarxiv-cs-cv

Efficient Adaptation of LLMs for Hate Speech Detection in Low-Resource Languages: A Comparative Study on Roman Urdu

arXiv:2608.18142v1 Announce Type: new Abstract: It is challenging to detect hate speech in Low Resource Languages (LRLs) because of the absence of annotated data, the informality of its language struc

Efficient INT8 Inference of Small NLP Models on Server CPUs with PyTorch Native Stack

arXiv:2608.18182v1 Announce Type: new Abstract: Small NLP models, especially BERT-family encoders, remain important in industrial workloads such as classification, ranking, and retrieval even in the e

researcharxiv-cs-cl

Event-Causal RAG: A Retrieval-Augmented Generation Framework for Long Video Reasoning in Complex Scenarios

arXiv:2605.06185v2 Announce Type: replace Abstract: Large vision-language models perform well on short- and medium-length video understanding but still struggle to maintain coherent event memory and r

Execution-grounded evaluation reveals hidden failures in language-model calculations for environmental science

arXiv:2608.18726v1 Announce Type: new Abstract: Large language models are increasingly used for quantitative work in the environmental sciences, yet existing evaluations score only final answers, leav

Eyes on the Image: Gaze Supervised Multimodal Learning for Chest X-ray Diagnosis and Report Generation

arXiv:2508.13068v2 Announce Type: replace Abstract: Medical vision-language models still struggle to match radiologists' attention and to verbalize findings with explicit spatial grounding. We address

First-Token Broadcasters: Mechanistic Origins of Language Identity and Distributed Robustness in Transformers

arXiv:2606.22361v2 Announce Type: replace-cross Abstract: Why do multilingual language models sometimes generate in the wrong language, and why is this so hard to fix? We introduce Language Identity H

Formal Verification of Romanov's Triplet Logic: A Verified Filter for Sliding-window 3-CNF with Application to Structured Formulas

arXiv:2608.18445v1 Announce Type: cross Abstract: We present the first mechanised formalisation of Romanov's Triplet Logic (TLS) in the Rocq proof assistant. TLS is a triplet-based combinatorial frame

researcharxiv-cs-ai

From Storage to Access: Verifiable Activation of Parametric Knowledge in LLMs via Explicit Priming and Implicit Reasoning

arXiv:2608.18581v1 Announce Type: cross Abstract: Although Large Language Models (LLMs) encode rich factual knowledge in their parameters, reliably recalling and verifying such knowledge remains a key

safetyarxiv-cs-ai

GenEx: A Graph-Based Representational Paradigm for SARS-CoV-2 Variant Detection via Codon Co-occurrence Networks

arXiv:2608.18238v1 Announce Type: new Abstract: Genomic analysis on viruses such as SARS-CoV-2 variants: Beta, Gamma, Delta, and Omicron is heavily dominated by classical bioinformatics methods, inclu

safetyarxiv-cs-ai

GS-VLA: Plug-and-Play Viewpoint Canonicalization for Frozen VLA Policies via Gaussian Splatting

arXiv:2608.19066v1 Announce Type: cross Abstract: This paper proposes a lightweight, plug-and-play framework that improves robustness to viewpoint shifts in Vision-Language-Action (VLA) policies witho

Human-Centric Intelligence in the Era of Foundation Models: A Survey

arXiv:2608.18184v1 Announce Type: new Abstract: Human-centric intelligence is evolving in the foundation-model era, with growing emphasis on scale, transferability, and general-purpose modeling. Yet i

researcharxiv-cs-cv

Hybrid ANN-SNN Pipeline with Local Plasticity

arXiv:2606.20151v2 Announce Type: replace-cross Abstract: This work proposes a hybrid ANN-SNN pipeline that effectively leverages the rich embeddings of pretrained artificial neural networks (ANNs) to

Impact of Iterative Fine-Tuning on Transcription Accuracy in Complex Historical Sanskrit Manuscripts

arXiv:2608.18696v1 Announce Type: cross Abstract: Digitizing the text from handwritten historical manuscripts is required to make them easily accessible, preservable, and to enable historical scholars

Introducing the Privacy-HSD Trade-off: Hate Speech Detection, but not at the Cost of Privacy

arXiv:2608.19006v1 Announce Type: new Abstract: Hate speech is a real and timely threat that affects a large portion of online users, especially youth and minority groups. While building reliable and

JSL-DC: A Word-Level Japanese Sign Language Dataset with Linguist-Derived Descriptions for Distinguishing Confusable Signs

arXiv:2608.18412v1 Announce Type: new Abstract: Effective sign language (SL) acquisition is crucial for deaf children, yet 95% are born to hearing parents who often lack proficiency in SL. SL recognit

LACONIC: Dense-Level Effectiveness for Scalable Sparse Retrieval via a Two-Phase Training Curriculum

arXiv:2601.01684v2 Announce Type: replace-cross Abstract: While dense retrieval models have been the standard for state-of-the-art information retrieval, their deployment is often constrained by high