Search: “benchmark”

Context-Aware Pre-Deployment Evaluation of AI Systems: A Regulatory Framework for Nigerian Fintech

arXiv:2609.24016v1 Announce Type: new Abstract: Commercial large language models are increasingly deployed across African fintech infrastructure for fraud detection and customer communication, yet no

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Controlling risks of AI in chemical science with agents

DGX agent

arXiv:2312.06632v2 Announce Type: replace Abstract: Artificial intelligence is rapidly advancing scientific discovery, but this progress carries risks of misuse, such as the creation of harmful substa

model-releasesarxiv-cs-ai

23 Sept 2026

CoVeR: Coverage-Based Routing of Verifier Calls in Agentic Retrieval

arXiv:2609.26086v1 Announce Type: new Abstract: An agentic retrieval system issues a sequence of search queries and must decide, at each step, whether the evidence collected so far is enough to stop.

Local Ai

CREDO: Variance-Guided Rubric Evolution for Replay-Corrected Credit Assignment

arXiv:2609.24174v1 Announce Type: new Abstract: Long-horizon language agents receive sparse terminal feedback, while intermediate rubrics provide structured but potentially misspecified assessments of

local-aiarxiv-cs-ai

CricRAG: Retrieval Augmented Vision-Language Models for Personalized Cricket Coaching

arXiv:2609.26056v1 Announce Type: new Abstract: Vision-Language Models (VLMs) offer promising capabilities for automated sports coaching but face a fundamental limitation: they implicitly compare agai

safetyarxiv-cs-cv

DeceptionAnalyser: A Web-Based AI Tool for Performing Structured Deception Analysis with Argumentation Schemes and LLMs

arXiv:2609.24369v1 Announce Type: cross Abstract: Deception plays a central role in Intelligence operations, yet it remains difficult to analyse systematically without expert knowledge of reasoning pa

Deepfakes and Synthetic Media: Generation, Detection, and Governance

arXiv:2609.25017v1 Announce Type: new Abstract: Deepfakes, synthetic audiovisual content produced by deep generative models, have escalated into a critical threat across civilian and military domains,

safetyarxiv-cs-cv

Diffusion-Induced Spatial Attention Overlapping Community Detection

arXiv:2609.26737v1 Announce Type: cross Abstract: Detection of overlapping communities is essential for modelling networks in which nodes participate simultaneously in multiple structural or functiona

Directional Total Variation-Regularized Implicit Neural Representations (DTV-INR) for Continuous Super-Resolution in Degraded Imaging Domains

model-releasesarxiv-cs-cv

arXiv:2609.25429v1 Announce Type: new Abstract: In this paper, we introduce the Directional Total Variation-Regularized Implicit Neural Representation (DTV-INR), an advanced variational paradigm that

Local Ai

Discovery-Driven Integration of Disjoint Tables via Text

arXiv:2609.26658v1 Announce Type: cross Abstract: Integrating heterogeneous datasets within data lakes is a critical challenge, particularly for semantically related tables that lack the explicit attr

local-aiarxiv-cs-cl

Discrete vs. Continuous: A Comprehensive Study of Unified Audio Understanding in LALMs

arXiv:2609.22851v2 Announce Type: cross Abstract: Large Audio Language Models (LALMs) utilize either continuous features or discrete tokens, yet the optimal representation paradigm for general audio u

DocMIDE: Learning Multi-Hop Implicit Derivation in Visually Rich Documents

arXiv:2609.24092v1 Announce Type: new Abstract: Real-world document processing systems rely on rigid, predefined schemas, yet critical target fields often lack direct visual counterparts on the page.

Domain-Adaptive Pretraining Enhances Water Treatment Semantic Representation for Large-Scale Structured Literature Mining

arXiv:2609.26034v1 Announce Type: new Abstract: Water treatment research is expanding rapidly, but much of the knowledge acquired from this research remains scattered across unstructured literature. T

Efficient Iterative Retrieval with Heterogeneous Batching

arXiv:2609.25405v1 Announce Type: cross Abstract: Modern information retrieval increasingly employs both embedding and generative models to handle complex queries. However, current serving systems suf

Enriching Speech Emotion Representations with Conversational Context

arXiv:2609.26422v1 Announce Type: new Abstract: Detecting emotions is necessary for building systems that can accurately and adaptively interact with humans. Speech Emotion Recognition (SER) has becom

EquivSVA: A Formally Verified Dataset of Behavioral Assertions Across Equivalent RTL Implementations

arXiv:2609.26751v1 Announce Type: new Abstract: Large language models are increasingly used to generate SystemVerilog Assertions from natural-language specifica- tions and register-transfer-level desi

Evaluating Accuracy and Probabilistic Reliability of Zero-Shot Time Series Foundation Models

arXiv:2609.25788v1 Announce Type: new Abstract: Time Series Foundation Models (TSFMs) promise a paradigm shift toward zero-shot forecasting by eliminating task-specific training. However, existing wor

Evidence-gated multimodal parsing and vectorization of architectural floor plans

model-releasesarxiv-cs-cv

arXiv:2609.25615v1 Announce Type: new Abstract: Architectural floor plans remain a high-friction barrier to archive digitization and early design-model preparation because heterogeneous graphics encod

eXplaining to Learn (eX2L): Regularization Using Contrastive Visual Explanation Pairs for Distribution Shifts

arXiv:2605.06368v2 Announce Type: replace-cross Abstract: Despite extensive research into mitigating distribution shifts, many existing algorithms yield inconsistent performance, often failing to outp

Applications

Faithful Faithfulness Evaluations: Challenges & Pitfalls Learned from a Breast MRI Case Study

arXiv:2609.25978v1 Announce Type: cross Abstract: Saliency maps are widely used to explain deep learning predictions in medical imaging, yet visually plausible explanations do not necessarily reflect

applicationsarxiv-cs-lg

Federating Quantum and Classical Computing: A Privacy-Preserving Hybrid Approach

arXiv:2609.25082v1 Announce Type: new Abstract: Quantum machine learning (QML) is increasingly recognized as one of the most promising near-term applications of quantum computing, viewed as a next-fro

Hardware

Flash-dLLM: IO-Aware KV Caching and Parallel Decoding for Fast, Memory-Efficient Diffusion LLMs

arXiv:2609.26796v1 Announce Type: new Abstract: Diffusion Large Language Models (dLLMs) have recently emerged as a promising alternative to autoregressive LLMs by enabling non-autoregressive text gene

hardwarearxiv-cs-cl

Tutorials

FoMo: Forking Moment in Generative Trajectory as a Perceptual Distance

arXiv:2609.25716v1 Announce Type: new Abstract: Reference-based image quality assessment (IQA) metrics aim to reflect how humans perceive the perceptual distance between a pair of images. To learn how

tutorialsarxiv-cs-cv

From Capability to Assurance in Autonomous Penetration-Testing Harnesses: A Framework and Reference Implementation

arXiv:2609.22664v1 Announce Type: cross Abstract: Research on large language model agents for penetration testing is evaluated almost entirely by capability: whether the agent captures a flag or repro

From Code to Requirements: Agentic Reverse Engineering of Business Rules at Enterprise Scale

arXiv:2609.22719v1 Announce Type: cross Abstract: Business requirements for enterprise software systems are rarely captured in structured form; the logic resides instead in source code, configuration

From Experts to Sub-experts: Fine-grained Parameter-Efficient Fine-Tuning for MoE LLMs

arXiv:2609.25655v1 Announce Type: new Abstract: As large language models (LLMs) scale rapidly, dense full-parameter adaptation becomes increasingly expensive, motivating sparse and modular architectur

From Pattern Recognizers to Personalized Companions: A Survey of Large Language Models in Mental Health

arXiv:2609.25186v1 Announce Type: cross Abstract: The rising global prevalence of mental health conditions, together with longstanding barriers in traditional healthcare, such as limited resources, hi

agentsarxiv-cs-cl

From Tone to Trajectory: Continuous Sentiment and the Shape of Monetary Policy Communication

arXiv:2609.25034v1 Announce Type: new Abstract: Central bank press conferences are not merely information releases --- they are structured narratives. We study whether the shape of sentiment within a

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From Utterances to Networks: Modelling Slang Adoption and Diffusion Across Subreddits

arXiv:2609.25669v1 Announce Type: new Abstract: Adoption and diffusion of neologisms in online communities have received renewed attention in recent years. As internet slang terms such as APT, referri

FuncCode: Compressing Kolmogorov--Arnold Networks in Function Space with Hardware-Aware Quantization

arXiv:2609.26067v1 Announce Type: new Abstract: Kolmogorov--Arnold Networks (KANs) replace scalar edge weights with learnable univariate functions, increasing flexibility but also parameter memory bec

Research

GaitVista: Reliability-Aware AI Measurement toward Accessible Longitudinal Gait Assessment

arXiv:2609.22619v1 Announce Type: new Abstract: Tracking recovery of walking function requires detecting meaningful gait change across rehabilitation sessions, yet objective 3D measurement remains con

researcharxiv-cs-ai

GDLAM: Group-Disentangled Latent Action Model for Highly Disentangled Embodied Pretraining

arXiv:2609.26118v1 Announce Type: new Abstract: Latent action models (LAMs) learn action-related representations from action-free videos via self-supervised future prediction, offering a scalable para

safetyarxiv-cs-ro

Glucose-ML: A collection of longitudinal diabetes datasets for development of robust AI solutions

arXiv:2507.14077v2 Announce Type: replace-cross Abstract: Artificial intelligence (AI) algorithms are a critical part of state-of-the-art digital health technology for diabetes management. Yet, access

Graph Memory for LLM Agents: At What Cost? A Comparative Evaluation of Query, Ingest, and Update Performance Across Graph Database Engines

arXiv:2609.23315v1 Announce Type: cross Abstract: Graph databases are frequently positioned as categorically necessary for connected-data workloads, yet the systems dimension along which they actually

Hardware

Greedy Decoding Is Not Precision-Invariant: Cross-Precision Output Divergence in LLM Inference

arXiv:2609.26621v1 Announce Type: new Abstract: Greedy decoding from large language models is commonly treated as deterministic. We show it is not precision-invariant: the same model, prompt, and deco

hardwarearxiv-cs-lg

GRUET: Quantifying Uncertainty of Agentic Reasoning-and-Acting Processes

arXiv:2609.24831v1 Announce Type: new Abstract: Agents have attracted considerably increasing attention due to the power of executing both Reasoning and Acting (ReAct) in open and dynamic environments

agentsarxiv-cs-ai

GTR: Gated Token Recurrence for Efficient Dense Prediction

arXiv:2609.26590v1 Announce Type: cross Abstract: Self-attention-based vision backbones perform well on dense prediction, but the quadratic computational cost of global softmax attention limits their

Hierarchical Floorplan-Guided Vision-Language Exploration for Embodied Question Answering

arXiv:2609.26360v1 Announce Type: new Abstract: Embodied Question Answering (EQA) requires an agent to explore a previously unseen environment, gather relevant information, and answer questions about

agentsarxiv-cs-ro

Hierarchical Sparse Bayesian Multitask Learning for Disease Prediction in Pooled Microbiome Studies

arXiv:2502.02552v2 Announce Type: replace Abstract: This paper proposes a hierarchical Bayesian multitask learning model that is applicable to the general multi-task binary classification learning pro

ICDAR2026 Competition on Multimodal Reasoning over Documents in Multiple Domains

arXiv:2609.25055v1 Announce Type: new Abstract: In this report we present results of the ICDAR2026 Competition on Multimodal Reasoning over Documents in Multiple Domains. This competition aimed to adv

agentsarxiv-cs-cl

Tutorials

In-Context Guidance: Learning Inter-Task Synergies via Numerical Foundational Models for Few-Shot Multitask Optimization

arXiv:2609.25836v1 Announce Type: new Abstract: Multi-task optimization (MTO) addresses a set of optimization tasks simultaneously, often suffering from inaccurate inter-task relationship estimation u

tutorialsarxiv-cs-lg

Information-Theoretic Decoupled Prompt Tuning for Continual Learning

arXiv:2609.26257v1 Announce Type: new Abstract: Continual learning (CL) aims to incrementally acquire knowledge from sequential data while avoiding catastrophic forgetting. Recently, prompt tuning has

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Local Ai

Informed Masking: Structure-Aware Perturbation for Reinforcement Learning in Diffusion Large Language Models

arXiv:2609.25927v1 Announce Type: new Abstract: Diffusion Large Language Models (dLLMs) have emerged as an efficient alternative to autoregressive models, yet aligning them via Reinforcement Learning

local-aiarxiv-cs-cl

Applications

JAMPR+/L2D: scalable neural heuristic for constrained vehicle routing problems in dynamic environment

arXiv:2609.26275v1 Announce Type: new Abstract: The vehicle routing problems with real-world constraints (we consider vehicles capacity limits, time windows constrains, pickup-and-delivery multi-depo

applicationsarxiv-cs-lg

LADDER: Graph-Guided Diffusion Language Models for Efficient Multi-Hop Reasoning

arXiv:2609.24346v1 Announce Type: new Abstract: Graph Retrieval-Augmented Generation (GraphRAG) has remarkably enhanced large language models on complex reasoning by leveraging structured entity topol

safetyarxiv-cs-ai

Layout-Guided Masking for GROBID: Lightweight Structural Gains in Large-Scale Scientific PDF Ingestion

arXiv:2609.26381v1 Announce Type: new Abstract: Transforming scholarly PDFs into machine-readable fulltext remains a bottleneck for large-scale information systems. Recent vision-based parsers improve

LEAP-NBV: Lightweight Edge Active-Perception for Foundation-Model Next-Best-View Planning

arXiv:2609.23974v1 Announce Type: new Abstract: Foundation models are endowing autonomous systems with greater intelligence, enabling a more comprehensive understanding of the environment through visu

LIMIT: Less Is More for Instruction Tuning in Text-to-SQL

arXiv:2609.24186v1 Announce Type: new Abstract: Large language models have achieved remarkable progress on Text-to-SQL through reasoning-enhanced fine-tuning, yet existing approaches predominantly rel