Search: “research”

A Time-Based Readout for Vector-Matrix Multiplication in Fully Analog Memristive SNNs

arXiv:2609.11713v1 Announce Type: cross Abstract: Artificial neural networks rely on vector-matrix multiplications (VMMs), whose implementation in von Neumann architectures is dominated by costly data

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Research

ActMap: Single-Pass Uncertainty Quantification from Generation-Time Activation Maps

DGX agent

arXiv:2609.11498v1 Announce Type: new Abstract: Practical uncertainty quantification (UQ) for large language models must decide, from a single generation, whether a specific answer should be trusted.

researcharxiv-cs-ai

12 Sept 2026

AI Soccer Analyst: Stage-Aware and Verifiable Human-AI Collaboration for Soccer Data Analysis

arXiv:2609.11224v1 Announce Type: cross Abstract: Sports data analysts translate domain questions into insights by combining computation with sport-specific domain expertise. Large language models eas

Architecting the Secure AI-SOC: A Neurosymbolic Framework for Pipeline Integrity and Threat Mitigation

arXiv:2609.10707v1 Announce Type: cross Abstract: The integration of Large Language Models (LLMs) into Security Operations Centers (SOCs) streamlines threat intelligence but introduces critical vulner

Model Releases

Benchmark Radar: A Living Database and Search Engine for AI Benchmarks and Evaluation

model-releasesarxiv-cs-ai

arXiv:2609.11115v1 Announce Type: new Abstract: Benchmark researchers and developers of large language models (LLMs) and other AI systems need to find relevant evaluations, locate their benchmark data

Model Releases

Best AI subscription for the dollar? What’s the best to spend on? ChatGPT or Claude or Gemini?

I’ve been researching which models to sub to and I’m currently not subbed to anything. I’ve definitely searched here and other places for opinions but a lot of what I was reading wasn’t current or 6mo

model-releasesr-chatgpt

Breaking Predictions Is Not Enough: Specified-Foil Counterfactuals for Temporal Graphs

arXiv:2609.11170v1 Announce Type: new Abstract: Temporal graph counterfactual explanations typically change past events to change or invalidate an original prediction, while leaving its replacement un

Calibration-Aware Uncertainty Cascades for Efficient Heterogeneous Model Collaboration

arXiv:2609.11446v1 Announce Type: new Abstract: Heterogeneous model collaboration seeks to exploit the complementary strengths of different models to balance predictive performance and inference cost.

Ceci n'est pas une pipe: AI systems as semantic abstractions

arXiv:2607.09489v2 Announce Type: replace Abstract: An AI system's output is not the fact or world state it appears to describe, but rather an engineered representation. We propose a semantic framewor

Deep-Fake CAPTCHA: Mitigating Next-Generation Social Engineering Attacks

arXiv:2609.11404v1 Announce Type: cross Abstract: This paper presents DF-CAPTCHA, an active defense against real-time deepfake impersonation in voice and video calls. Instead of passively searching fo

Discovering Temporal Structure: An Overview of Hierarchical Reinforcement Learning

arXiv:2506.14045v2 Announce Type: replace Abstract: Developing agents capable of exploring, planning and learning in complex open-ended environments is a grand challenge in artificial intelligence (AI

Exploring Diffusion Transformers for Cross-Modal Augmentation in Multimodal Brain State Decoding

arXiv:2609.11341v1 Announce Type: new Abstract: Multimodal brain state decoding has largely focused on fusing paired modalities for prediction, but has rarely explored how their correspondence can be

Exploring Second-Order Pattern Recognition in Speaker Recognition

arXiv:2609.11182v1 Announce Type: cross Abstract: In classical pattern recognition tasks, neural networks are trained to recognise human-defined patterns for model inputs. Some Explainable AI (XAI) me

Extending SMT Solving with Non-Ground Clause Learning

arXiv:2609.11509v1 Announce Type: new Abstract: Quantifier instantiation is currently the main approach to non-ground SMT solving: solvers generate ground instances and solve the resulting ground SMT

Four Generations of Quantum Biomedical Sensors

arXiv:2603.29944v3 Announce Type: replace-cross Abstract: Quantum sensing technologies offer transformative potential for ultra-sensitive biomedical sensing, yet their clinical translation remains con

How LLMs Follow Instructions: Skillful Coordination, Not a Universal Mechanism

arXiv:2604.06015v2 Announce Type: replace Abstract: Instruction tuning is commonly assumed to endow language models with a domain-general ability to follow instructions, yet the underlying mechanism r

I love this and really hope we can come together as an industry and make it happen.

I love this and really hope we can come together as an industry and make it happen. We Must Pace the Frontier: I’ve written a new essay on why the AI industry should slow down, with a three-part plan

researchkarpathy--x

Investigating catastrophic forgetting in sound event classification

arXiv:2609.11447v1 Announce Type: cross Abstract: This work investigates a number of approaches to prevent catastrophic forgetting in class incremental learning scenarios for sound event classificatio

Less can be More: What Aspects of Speech Drive End-of-Turn Detection

arXiv:2609.11066v1 Announce Type: cross Abstract: In conversational AI, detecting when a speaker has finished talking is crucial for natural turn taking. While recent work incorporates semantics, the

Agents

Magenta: Closing the Loop Between Mathematical Reasoning and Lean Verification

arXiv:2609.11319v1 Announce Type: new Abstract: Most of mathematical knowledge has been communicated through so-called informal use of mathematics and natural language. With large language models (LLM

agentsarxiv-cs-ai

On the Regularization Landscape for the Linear Recommendation Models

arXiv:2609.11876v1 Announce Type: new Abstract: Recently, a wide range of recommendation algorithms inspired by deep learning techniques have emerged as the performance leaders on several standard rec

Rescaling Confidence: What Scale Design Reveals About LLM Metacognition

arXiv:2603.09309v3 Announce Type: replace Abstract: Verbalized confidence, in which LLMs report a numerical certainty score, is widely used to estimate uncertainty in black-box settings, yet the confi

RouteRepair: Instance-Level Failure Diagnosis and Targeted Repair in LLM-Based Automated Heuristic Design for Routing Optimization

arXiv:2609.11452v1 Announce Type: new Abstract: Efficient routing optimization is essential to freight transportation, urban logistics, and shared mobility, where high-quality heuristics are often req

Routing by Reasoning Need: Trajectory-Aware Decoding Control for Diffusion Vision-Language Models

arXiv:2609.11315v1 Announce Type: new Abstract: Diffusion vision-language models generate answers through iterative refinement, exposing intermediate answer trajectories that can be inspected and cont

Warrant Theory

arXiv:2609.11667v1 Announce Type: cross Abstract: In this paper, we develop warrant theory as a philosophical discipline concerned with the inferential legitimacy of propositions within logical analys

X-RACE: XAI-assisted Recurrent neural network Attribution for Channel Estimation

arXiv:2609.11211v1 Announce Type: cross Abstract: Deep learning models, notably Long Short-Term Memory (LSTM), have demonstrated promising performance in channel estimation for high-mobility vehicular

3D Point Splatting for mmWave Radar Novel View Synthesis

arXiv:2609.11894v1 Announce Type: new Abstract: Solving novel view synthesis (NVS) for millimeter-wave (mmWave) radar requires a renderer that is physically faithful, complex-valued, and multi-viewpoi

A Comparative Evaluation of Pre-trained Convolutional Neural Networks for Melanoma Detection

arXiv:2609.11550v1 Announce Type: new Abstract: Early diagnosis of melanoma is critical for improving patient survival rates. However, accurately distinguishing melanoma from other skin lesions remain

A Group-Based Resource Allocation Model for the Fractional Knapsack Problem

arXiv:2609.06470v2 Announce Type: replace-cross Abstract: To solve the fractional knapsack problem, Dantzig's greedy rule orders items according to their value-to-cost ratio. This ordering introduces

A Multi-Stage Rule-Chaining Framework for Compositional and Interpretable Cognitive Reasoning

arXiv:2609.10654v1 Announce Type: cross Abstract: The Abstraction and Reasoning Corpus (ARC) benchmarks cognitive generalization, the ability to infer and apply abstract rules from limited examples. T

A Multi-View and Confusion-Guided Ensemble Framework for Robust Synthetic Image Attribution

arXiv:2609.11188v1 Announce Type: new Abstract: Synthetic image attribution (SIA) has become increasingly important with the rapid advancement of text-to-image generation models. However, accurately i

A Quantum-Inspired Dequantization Method for Diagonally Weighted Matrix Functions: Application to Learning with Optimized Random Features

arXiv:2609.10729v1 Announce Type: cross Abstract: Quantum-inspired classical algorithms have dequantized several quantum machine learning routines by replacing quantum linear-algebra subroutines with

A Two-Mirror Faceted Projection System for EUV Lithography

arXiv:2609.11299v1 Announce Type: cross Abstract: We propose an all-reflective two-mirror projection system for extreme ultraviolet (EUV) lithography operating at exposure wavelengths of 13.5~nm (Mo/S

A variational physics-informed graph neural network for heterogeneous solid mechanics

arXiv:2609.10983v1 Announce Type: cross Abstract: Stress localization in heterogeneous solids is governed by the bimaterial interface, where the displacement field remains C^0-continuous, while in-pla

Active noise cancellation on open-ear smart glasses

arXiv:2604.05519v2 Announce Type: replace-cross Abstract: Active noise cancellation (ANC) is widely deployed on consumer headphones and earbuds to suppress environmental noise. However, existing ANC s

Adaptive Margin Ordinal Loss: Penalizing Center-Class Hedging in Ordinal Classification

arXiv:2609.10752v1 Announce Type: new Abstract: Standard cross-entropy loss causes neural networks trained on ordinal classification tasks to hedge predictions toward center classes, a failure mode we

Addressing A Posteriori Performance Degradation in Neural Network Subgrid Stress Models

arXiv:2511.17475v2 Announce Type: replace-cross Abstract: Neural network subgrid stress models often have a priori performance that is far better than the a posteriori performance, leading to neural n

Automated multi-class wound assessment using dedicated instance segmentation models for boundary detection and classification

arXiv:2603.27325v2 Announce Type: replace Abstract: Accurate wound classification (WC) and boundary segmentation are essential for guiding clinical decisions in chronic and acute wound management. How

BiHDTrans: binary hyperdimensional transformer for efficient multivariate time series classification

arXiv:2509.24425v2 Announce Type: replace Abstract: The proliferation of Internet-of-Things (IoT) devices has led to an unprecedented volume of multivariate time series (MTS) data, requiring efficient

BridgeMatch: Conditional Transport Bridges in Matching Matrix Space for 3D Deformable Registration

arXiv:2609.11472v1 Announce Type: new Abstract: Reliable non-rigid point cloud correspondences are important for deformable anatomical registration, embodied perception and manipulation, and dynamic 3

Byzantine-Robust Federated Fire Detection with a Rotating Coordinator

arXiv:2609.10647v1 Announce Type: new Abstract: We study the application of federated learning (FL) to indoor fire detection. Such fire-detection systems use edge cameras that record sensitive footage

Characterizing Narrative Content in Web-scale LLM Pretraining Data

arXiv:2606.19468v2 Announce Type: replace Abstract: The narrative composition of web-scale LLM pretraining corpora remains largely unexplored, even though narrative is a fundamental mode of human comm

CHRONOBERG: Capturing Language Evolution and Temporal Awareness in Foundation Models

arXiv:2509.22360v2 Announce Type: replace Abstract: Large language models (LLMs) excel at operating at scale by leveraging social media and various data crawled from the web. Whereas existing corpora

Coherent Floquet quantum reservoirs for molecular property prediction

arXiv:2609.11071v1 Announce Type: cross Abstract: Quantum reservoir computing (QRC) uses quantum dynamics to represent input histories for prediction through a trained classical readout. Discrete time

Complex-Text Robustness Evaluation and Failure Diagnosis for Low-Resource Multilingual Text-to-Speech

arXiv:2609.11545v1 Announce Type: new Abstract: Low-resource multilingual text-to-speech (TTS) systems have expanded language coverage, but their robustness under complex text inputs remains insuffici

Conformal Calibration Transfer

arXiv:2609.10737v1 Announce Type: new Abstract: Conformal prediction converts point predictions into set-valued predictions with coverage guarantees under exchangeability between calibration and deplo

Counterfactual Marginalisation: Framework for Evaluating Robustness to Nuisance Variables

arXiv:2609.10778v1 Announce Type: new Abstract: Machine learning models can achieve strong test performance while relying on demographic or acquisition-related shortcuts. We propose counterfactual (CF

Agents

Data-Efficient Language Modeling: From Frontier Advancement to Principle-Guided Model Improvement

arXiv:2609.10702v1 Announce Type: new Abstract: Learning from limited text requires models to use context, generalize to new inputs, and retain useful capabilities. Qiushi Engine conducted a long-hori

agentsarxiv-cs-cl