Search: “models”

VEX-Bench: Benchmarking Verification Complexity of LLM-Generated Misinformation

arXiv:2609.35028v1 Announce Type: new Abstract: Large language models (LLMs) have made misinformation inexpensive to produce but not to verify, creating a growing asymmetry in the information ecosyste

29 Sept 2026

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Local Ai

'Where Can I Trust You?': Boundary-Aware Evaluation of Surrogate Fidelity

DGX agent

arXiv:2609.32230v1 Announce Type: new Abstract: Surrogate models are commonly evaluated by how often they agree with their teacher model over an evaluation set. Local variation in this agreement is we

local-aiarxiv-cs-lg

29 Sept 2026

WhiteCon: Semi-Supervised Domain Adaptation Regression Through Whitening Transform and Dual Consistency

arXiv:2609.34078v1 Announce Type: new Abstract: Domain adaptation is crucial for addressing distributional shifts that degrade model performance across domains. While most existing research has center

29 Sept 2026

Agents

Auditing Latent-Space Monitors for Autonomous Driving

arXiv:2609.30557v1 Announce Type: cross Abstract: Runtime failure monitors can use a model's internal representations to anticipate failures. We audit this monitoring strategy across two autonomous-dr

agentsarxiv-cs-ai

AuthGuard-R: Safety-Compliant Mission Hijacking and Dual-Gate Defense for LLM-Controlled Robots

model-releasesarxiv-cs-ro

arXiv:2609.31110v1 Announce Type: new Abstract: Large language models are increasingly used as high-level planners for mobile robots, robot manipulators, and autonomous vehicles. Recent studies show t

Benchmarking the Connectomes of Caenorhabditis elegans within the Reservoir Computing Framework

arXiv:2609.30508v1 Announce Type: new Abstract: The aim of this work is to examine the connectomes of Caenorhabditis elegans through a computational lens using the reservoir computing framework. Conne

Tutorials

Combining General and Domain-Specific Pretext Tasks for Brain MR Image Segmentation

arXiv:2609.30708v1 Announce Type: cross Abstract: A key challenge in medical image analysis is the scarcity of large annotated datasets for specific populations and diseases. As deep learning models r

tutorialsarxiv-cs-ai

Applications

Cost-Aware Best-LLM Identification using Dueling Feedback

arXiv:2609.30360v1 Announce Type: cross Abstract: Inspired by the problem of identifying the best model from a collection of large language models (LLMs) with heterogeneous querying costs, we formulat

applicationsarxiv-cs-ai

Cross-Backend QIEO: Universal Runtime Portability across OpenMP5, CUDA, HIP, and Multi-Language Interfaces

arXiv:2609.30914v1 Announce Type: cross Abstract: Quantum-inspired algorithms emulate quantum mechanical principles, such as, superposition, interference, and probabilistic amplitude evolution, on cla

Differentiable RNA Secondary Structure Extraction for Deep Learning

arXiv:2609.30752v1 Announce Type: new Abstract: Many deep learning approaches to RNA secondary structure prediction have recently been proposed. They typically output a weight matrix W where W_{ij} is

researcharxiv-cs-lg

Evidence-Grounded Auditing of Identification Assumptions in Climate-Policy Causal Evaluations

arXiv:2609.30867v1 Announce Type: new Abstract: Difference-in-differences (DID) studies are widely used to evaluate climate policy, but assessing the evidence supporting their identification assumptio

FedHisto-PAST: Parameter-Efficient Stain-Aware Federated Learning for Cross-Site Lung Histopathology Classification

arXiv:2609.31150v1 Announce Type: cross Abstract: Cross-site lung histopathology classification must account for stain variation, non-IID client data, missing classes, and the cost of adapting large p

Game Arena: Strategic LLM Evaluation in Competitive Environments

arXiv:2609.31473v1 Announce Type: new Abstract: We introduce Kaggle Game Arena, an open and ever-expanding platform to evaluate large language models (LLMs) through competitive games. Different from s

researcharxiv-cs-ai

Gauss What You Need: Compact Gaussian Splatting Across Scene Scales

arXiv:2609.31248v1 Announce Type: new Abstract: 3D Gaussian Splatting reconstructs a scene as a collection of Gaussian primitives from a set of posed photographs called the capture. The number of prim

Highlight-Then-Summarize: Learning to Compress Evidence for Long-Context Understanding

arXiv:2609.31382v1 Announce Type: cross Abstract: Long-context understanding requires large language models (LLMs) to reason over lengthy documents, conversations, and code, yet task-relevant evidence

Interpretable-by-Design Descriptor Portfolios Match a 2048-Dimensional Foundation Embedding on Low-Data Molecular Assays

arXiv:2609.30789v1 Announce Type: new Abstract: In low-data structure-activity prediction, the choice of molecular representation can matter more than the choice of predictor, and tabular foundation m

researcharxiv-cs-lg

Metacognitive Selective Ensemble for Mobile Systems

arXiv:2609.31031v1 Announce Type: new Abstract: Deep ensembles improve robustness in mobile sensing, but repeatedly executing many models over continuous sensor streams is costly. Selecting only a few

researcharxiv-cs-lg

Muslim: A Deployed Arabic Voice AI Platform for Grounded Islamic Knowledge

arXiv:2609.31511v1 Announce Type: new Abstract: We present Muslim, a production Arabic voice AI platform serving grounded, sourced Islamic knowledge to real users. Beyond a real-time voice pipeline (N

On the Limits of Univariate Deep Learning for Significant Wave Height Forecasting

arXiv:2609.30688v1 Announce Type: cross Abstract: This study conducts a systematic hyperparameter search across five deep learning architectures, DLinear, LSTM, PatchTST, ResAttLstm, and Mamba2, and n

ORCA: Evaluating LLMs on Data Science Code Translation

arXiv:2609.30749v1 Announce Type: new Abstract: Data Science Code Translation (DSCT) is the process of converting code between data science libraries while preserving functional equivalence and enabli

Agents

Parameters vs. Context: TRACE Fine-Tuning for Robust Retrieval-Augmented Generation

arXiv:2609.30337v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) mitigates knowledge obsolescence and factual hallucination in large language models by introducing external context

agentsarxiv-cs-lg

Predicting Transmembrane Protein Topology from 3D Structure

arXiv:2609.30446v1 Announce Type: new Abstract: This paper presents a novel approach to infer protein topology using the state-of-the-art graph neural network (GNN), SchNet. The model is trained on th

researcharxiv-cs-ai

Safety

T-RoPE: Time-Aware Rotary Position Embedding for Sequential Recommendation

arXiv:2609.30576v1 Announce Type: new Abstract: Large-scale recommenders increasingly adopt the sequential generative recipe behind large language models, bringing the Transformer into recommendation

safetyarxiv-cs-ai

Towards Whole-Study Screening for Congenital Heart Disease in Fetal Ultrasound Using Multiple Instance Learning

arXiv:2609.31376v1 Announce Type: cross Abstract: Congenital heart disease (CHD) is the most common birth defect, yet a large fraction of cases remain undetected on prenatal ultrasound, in part becaus

researcharxiv-cs-cv

TrafficImag: A Benchmark for Counterfactual Roadside Traffic Video Generation

arXiv:2609.30722v1 Announce Type: cross Abstract: Existing roadside traffic datasets support perception, forecasting, and visual question answering, but they do not evaluate counterfactual video gener

ZooWork-ShopRanker: An Open, Preference-Aligned E-Commerce Reranker

arXiv:2609.31002v1 Announce Type: new Abstract: Open rerankers trained for general web retrieval transfer imperfectly to e-commerce, where ranking decisions depend not only on topical relevance but al

AI in Science: Early Insights

arXiv:2609.28504v1 Announce Type: cross Abstract: Scientific progress is a key driver of economic growth and prosperity. There is great excitement - but also concerns - about the impacts of AI on scie

Beyond Pairwise Attention: Higher-Order Modular Attention for Efficient Sequence Learning

arXiv:2603.11133v2 Announce Type: replace Abstract: Sequence modeling tasks can involve intrinsic higher-order dependencies, while standard self-attention assigns scores to token pairs and does not ex

BranchShine-CR: Compact Multilingual IPA Transcription with Self-Conditioned CTC and Consistency Regularization

arXiv:2609.29069v1 Announce Type: new Abstract: We introduce BranchShine-CR, a 25M-parameter model for multilingual transcription into the International Phonetic Alphabet (IPA). It combines log-mel fe

Combating Instruction Conflict via Energy-Driven Latent Conflict Detection

arXiv:2609.08646v2 Announce Type: replace Abstract: Large Language Models (LLMs) are increasingly deployed with hierarchical instructions, yet they remain vulnerable to conflicts in which user directi

ComplexSync: High-Fidelity and Real-Time Lip Sync in Complex Scenarios

arXiv:2609.29225v1 Announce Type: new Abstract: Lip synchronization aims to generate visual lip dynamics that align precisely with speech audio. Despite the high generation quality of diffusion models

Era by Eon: Benchmarking Enterprise Agents on Hidden Knowledge

arXiv:2609.30055v1 Announce Type: cross Abstract: In the Era by Eon benchmark, each question states the rules for its answer, and code computes the answer from a generated company's data. When agents

GPT-6-Astra Lights Up Embodied Navigation: Evaluation in Zero-Shot Vision-and-Language Navigation in Continuous Environments

model-releasesarxiv-cs-ro

arXiv:2609.29861v1 Announce Type: new Abstract: We investigate whether GPT-6-Astra, a general-purpose foundation model, can navigate unfamiliar environments using its own perception, reasoning, and de

Grammatical 'grandmother neurons' are rare in LLMs

arXiv:2609.29328v1 Announce Type: new Abstract: Understanding how Large Language Models (LLMs) encode linguistic structures remains a fundamental challenge in interpretability research. While diagnost

GRASP: Generating, Revising, and Assessing for Strategic Planning with Agentic AI

arXiv:2609.30147v1 Announce Type: new Abstract: Large Language Models (LLMs) typically exhibit a performance profile where reliability degrades as task complexity increases. We address the challenge o

IDRBench: Benchmarking the Interactive Capabilities of Deep Research Agents

arXiv:2601.06676v3 Announce Type: replace-cross Abstract: Large Language Model (LLM)-based deep research agents perform multi-step reasoning, web exploration, and long-form report generation. In these

Language Specificity vs. Domain Diversity: Benchmarking Transformers for Bangla Medical NER

arXiv:2609.29101v1 Announce Type: new Abstract: Medical Named Entity Recognition (NER) for low-resource languages remains a challenging task due to high linguistic variability and a scarcity of domain

Learning to Ideate for Scientific Impact

arXiv:2609.29802v1 Announce Type: new Abstract: Scientific ideation is increasingly mediated by large language models, but current ideation systems are usually trained and evaluated on immediately jud

researcharxiv-cs-ai

Looks the Same, Answers Differently: Flip-Direction Steering for Robust Vision-Language Reasoning

arXiv:2609.28851v1 Announce Type: new Abstract: Vision-language models (VLMs) achieve strong visual reasoning performance, yet subtle changes from routine image capture and processing can alter their

Tutorials

MorphIK: Morphology-Conditioned Neural Inverse Kinematics for Unknown Robots

arXiv:2609.29908v1 Announce Type: cross Abstract: Neural models can learn to generate various solutions to the inverse kinematics problem from data, but are usually limited to a single robot. We prese

tutorialsarxiv-cs-ai

Multimodal Thinking with Renderable Programs

arXiv:2609.30130v1 Announce Type: cross Abstract: Current vision-language models (VLMs) excel at visual content understanding and text-based reasoning, yet their structure limits the advancement of in

nicode{x1F493}Heartian: Physiology-Aware Relightable Gaussian Head Avatar

arXiv:2609.28539v1 Announce Type: new Abstract: Gaussian head avatars typically model intrinsic facial appearance as temporally static, omitting subtle cardiac-induced skin-color variation. We propose

PrivDrift: Auditing User-Secret Leakage Under Topic Drift in Active LLM Conversations

arXiv:2609.30094v1 Announce Type: new Abstract: Large language models increasingly operate as persistent assistants in user-facing, shared-session, and tool-augmented settings. When users disclose sen

Reconstructing short-lived particles using hypergraph representation learning

arXiv:2402.10149v3 Announce Type: cross Abstract: In collider experiments, the kinematic reconstruction of heavy, short-lived particles is vital for precision tests of the Standard Model and in search

Robust Detection of LLM-Generated Text under Contamination

arXiv:2609.29935v1 Announce Type: cross Abstract: We study the detection of LLM-generated text under editing and contamination. Modeling human and machine text as finite-order Markov processes with Hu

Safe Skill Retirement for Physical Agents

arXiv:2609.29543v1 Announce Type: new Abstract: Agent skills bundle procedural guidance with execution conditions governing authority, user consent, and live environment state. When model capabilities

Scoring Both Directions: LLMs realize the MRS they cannot reliably parse

arXiv:2609.30071v1 Announce Type: new Abstract: The English Resource Grammar (ERG) is a hand-written computational grammar of English. Given a sentence, its processor, ACE, produces a formal meaning r

Speculative Evaluation of Stochastic LLMs

arXiv:2609.28560v1 Announce Type: cross Abstract: Evaluating a stochastic large language model is costly: benchmark scores estimate expected performance from randomized rollouts, yet uniform repetitio