Search: “models”

Insurance Reserve Intelligence Platform

arXiv:2609.30765v1 Announce Type: new Abstract: Insurance reserve estimation is a fundamental actuarial task supporting premium pricing, solvency assessment, financial reporting, capital planning, and

Latent Generative Solvers for Generalizable Long-Term Physics Simulation

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arXiv:2602.11229v3 Announce Type: replace Abstract: Reliable physics simulation demands two capabilities that today's neural PDE solvers do not deliver together: generalization across heterogeneous PD

researcharxiv-cs-ai

28 Sept 2026

Learning to Replace MCMC in Split-Gibbs Diffusion Posterior Sampling via Deep Unfolding

arXiv:2609.30539v1 Announce Type: cross Abstract: Split Gibbs sampling enables diffusion posterior inference for general nonlinear inverse problems by decoupling prior and likelihood computations, all

Learning What to Skip: Counterfactual Credit Assignment for Efficient Multi-Agent LLM Workflows

arXiv:2609.30734v1 Announce Type: new Abstract: Multi-agent LLM workflows use planning, execution, verification, and summarization to improve task performance, yet the value of each component depends

LogicTree-RAG: Logic Tree-guided Retrieval-Augmented Generation for Long-form Patent Drafting

arXiv:2609.30943v1 Announce Type: new Abstract: Long-form technical text generation underpins knowledge-intensive workflows, yet remains challenging for large language models (LLMs) due to the need fo

ManiVid: Unified and Explainable Forensic Analysis of Manipulated Videos

arXiv:2609.30934v1 Announce Type: new Abstract: Rapid advances in AI-generated video (AIGV) have increased the risks posed by deceptive video manipulation. Unlike fully synthetic videos, manipulated v

NaijaNLP: A Survey of Nigerian Low-Resource Languages

arXiv:2502.19784v3 Announce Type: replace-cross Abstract: With over 500 languages in Nigeria, three languages - Hausa, Yoruba and Igbo spoken by more than 175 million people, account for about 65% of

NeuralCert: certified computational discovery of extremal mathematical constructions

arXiv:2609.30296v1 Announce Type: new Abstract: Neural networks are becoming popular in solving mathematical problems, but stochastic models do not provide mathematical exactness by themselves. This s

Nonparametric In-Context Learning under Growing Geometric Complexity: Minimax Optimality and Local Geometry-Adaptivity of Transformers

arXiv:2609.31458v1 Announce Type: cross Abstract: Transformers have become a central architecture for in-context learning (ICL), particularly through their state-of-the-art performance in large langua

Pocket-STVG: lightweight architecture for Spatio-Temporal Video Grounding

arXiv:2609.31135v1 Announce Type: cross Abstract: Spatio-Temporal Video Grounding (STVG) aims to localize the spatio-temporal tube in a video corresponding to a natural language query. While recent me

POIL: Point-based One-Shot Imitation Learning with Stable Dynamical Systems

arXiv:2609.30404v1 Announce Type: new Abstract: We present POIL, a point-based one-shot imitation learning framework with stable dynamical systems. While one-shot imitation avoids collecting extensive

researcharxiv-cs-ro

Population loss in shallow ReLU networks: Bias & families of critical points

arXiv:2609.30661v1 Announce Type: new Abstract: The main result presented is a formula for the population loss in the student-teacher kernel model that is applicable to shallow ReLU networks with bias

safetyarxiv-cs-lg

Pretrained ASR Pseudo-labeling for Noisy Police Audio

arXiv:2609.30469v1 Announce Type: new Abstract: Pretrained ASR systems perform poorly on noisy Broadcast Police Communication (BPC), hindering efforts to understand police decision-making. Pseudo-labe

Privacy-Preserving Prompted Policy Search for Robotic Control

arXiv:2609.30554v1 Announce Type: new Abstract: Large language models (LLMs) have recently demonstrated promising capabilities as in-context policy optimizers for Reinforcement Learning (RL), enabling

safetyarxiv-cs-ro

Purin: A Biology-inspired Mechanism for Artificial Neural Networks

arXiv:2609.31235v1 Announce Type: new Abstract: Artificial neural networks (ANNs) usually represent neural transmission with fixed trainable weights during a training batch, which omits short-term cha

RAPTOR: Ridge-Adaptive Logistic Probes

arXiv:2602.00158v3 Announce Type: replace-cross Abstract: Probing studies what information is encoded in a frozen LLM's layer representations by training a lightweight predictor on top of them. Beyond

Region-Level Black-Box Defense Against Stealthy Embedding-Space Backdoors in CLIP

arXiv:2609.31558v1 Announce Type: new Abstract: Contrastive Language--Image Pretraining (CLIP) has emerged as a dominant vision backbone due to its strong transferability and zero-shot capabilities. H

local-aiarxiv-cs-cv

Samples, Sources, Space: Decomposing Data Scale in Spatially Structured Representation Learning of Human Brain Microarchitecture

arXiv:2609.31201v1 Announce Type: new Abstract: Scaling studies typically represent training data by a single count of samples. For hierarchically and spatially structured data, however, the same numb

SkillEvoReg: Regularizing Agent Skill Evolution Against Overfitting

arXiv:2609.30861v1 Announce Type: new Abstract: Language-model agents increasingly improve by converting execution experience into reusable external skills. Yet repeated skill updates form a learning

agentsarxiv-cs-ai

Tutorials

Stable initialization without the CLT

arXiv:2609.30633v1 Announce Type: new Abstract: Successful training of deep neural networks is highly dependent on the distribution of the initial weights. If the weights are too large, network traini

tutorialsarxiv-cs-lg

Structured-Diffuser: Diffusion with Task-Conditioned Structured Priors for Motion Planning

arXiv:2509.25685v3 Announce Type: replace Abstract: We propose Structured-Diffuser, a diffusion planner that embeds task and motion structure directly into the noise model. Unlike standard diffusion-b

researcharxiv-cs-ro

The Shape of Events: Edge-Based Inductive Biases via Cross-Domain Distillation

arXiv:2609.30478v1 Announce Type: new Abstract: Convolutional neural networks trained on ImageNet are known to exhibit a strong preference for local high-frequency texture, an inductive bias that tran

local-aiarxiv-cs-cv

Towards Understanding Momentum Acceleration in River-Valley Loss Landscape

arXiv:2609.30957v1 Announce Type: new Abstract: The empirical success of pretraining large language models has inspired a deeper investigation into the underlying loss landscapes and the optimization

UniAR: A Unified Framework for Autism Recognition Enhanced by Multi-View Prompt Learning

arXiv:2609.31298v1 Announce Type: cross Abstract: Autism Spectrum Disorder (ASD) is a complex neurodevelopmental disorder for which early and accurate diagnosis is critical to improving long-term deve

Hardware

Universal Drift Correction for Multidimensional Scanning Microscopy

arXiv:2609.30866v1 Announce Type: cross Abstract: In scanning microscopy, drift causes the specimen to be sampled at positions displaced from the nominal probe positions. This displacement alters the

hardwarearxiv-cs-cv

Who Says What: Symbolic Trimodal Binding Mechanisms in Audio-Visual LLMs

arXiv:2609.31193v1 Announce Type: new Abstract: Current Audio-Visual LLMs (AVLLMs) struggle with reasoning over videos featuring multi-speaker dialogues. In such videos, resolving 'who says what' is c

Why Alzheimer's Speech Screening Fails to Generalize: Bridging the Deployment Gap via Cross-Corpus Evidence Anchoring

arXiv:2609.31293v1 Announce Type: cross Abstract: Speech-based screening is a promising, non-invasive approach for detecting Alzheimer's disease and related cognitive risks. However, models trained on

researcharxiv-cs-cl

A Fast and Effective Solution to the Problem of Look-ahead Bias in LLMs

arXiv:2512.06607v2 Announce Type: replace-cross Abstract: Applying LLMs to predictive tasks in finance is challenging due to look-ahead bias resulting from their training on long time-series data. Thi

safetyarxiv-cs-cl

ActGaze: Learning Action-Grounded Gaze through Counterfactual Visual Interventions for High-Precision Manipulation

arXiv:2609.28955v1 Announce Type: new Abstract: Current Vision-Language-Action (VLA) models often struggle with high-precision robotic manipulation. We attribute this limitation primarily to their vis

safetyarxiv-cs-ro

AdaHVLA: Adaptive Harnesses for Long-Horizon Vision-Language-Action Execution

arXiv:2609.29204v1 Announce Type: new Abstract: Vision-language-action (VLA) models offer strong local control and instruction following but often struggle with long-horizon tasks requiring persistent

agentsarxiv-cs-ro

AV-GRPO: Modality-Anchored Decoupling Diffusion Reinforcement Learning for Joint Audio-Video Generation

arXiv:2609.29816v1 Announce Type: new Abstract: Recent years have witnessed major progress in joint audio-video generation. Existing models still suffer from limited per-modality fidelity, insufficien

safetyarxiv-cs-cv

Breaking the Environment Wall: Evolving LLM Agent Environments for Recursive Self-Improvement

arXiv:2609.29773v1 Announce Type: new Abstract: Many real-world tasks (e.g., office workflows, scientific experimentation) require LLM agents to interact repeatedly with their environments for context

agentsarxiv-cs-ai

BRFID: Toward Byzantine-Robust Federated Intrusion Detection

arXiv:2609.28599v1 Announce Type: cross Abstract: Flipping 60% of training labels from a single Byzantine client using label-flipping model poisoning self-degrades an attacker's own federated detectio

Clinical Knowledge Graphs for Chest X-Ray Device Reasoning

arXiv:2609.29536v1 Announce Type: new Abstract: Chest radiographs are routinely used to verify the position of catheters, tubes, and other support devices. Existing image models often return labels or

Cross-Modal Emotion Understanding: A Transformer-GAT Approach for Dialogue Emotion Recognition

arXiv:2609.29556v1 Announce Type: new Abstract: Multimodal emotion recognition is a key research area in affective computing, with applications in sentiment analysis, intelligent customer service, and

Dense-Joint-Based Obstacle-Aided Locomotion with a Joint-Repositionable Snake Robot

arXiv:2609.29261v1 Announce Type: new Abstract: Obstacle-aided locomotion is a fundamental capability for snake robots to traverse complex environments. However, conventional rigid-link snake robots o

researcharxiv-cs-ro

DrGait: Biomechanically Grounded Visual Reasoning for Interpretable Clinical Gait Analysis

arXiv:2609.28796v1 Announce Type: cross Abstract: Current automated gait analysis for clinical applications relies on uninterpretable black-box classifiers. Although Vision-Language Models (VLMs) offe

agentsarxiv-cs-ai

Elucidating the Conformal Structure of the Brinkman Penalisation Method for Geometry-Adapted, Structure-Preserving Operator Learning of Hamiltonian PDEs

arXiv:2609.29847v1 Announce Type: cross Abstract: The Brinkman penalisation method embeds boundary-value problems on complex domains into a simple computational box by modeling the solid region as a s

EvoTreeNAD: Genealogy-Guided Evolution for LLM-Driven Neural Architecture Discovery

arXiv:2609.29016v1 Announce Type: cross Abstract: AI-driven scientific discovery accelerates research by autonomously developing solutions and designs. Large language model (LLM) agents support this p

agentsarxiv-cs-lg

Exploiting answer-invariant redundancies in satellite imagery for efficient VLM inference on edge

arXiv:2609.29029v1 Announce Type: new Abstract: Onboard vision-language models could enable satellites to answer queries directly, but exhaustive tiled inference over high-resolution imagery is slow a

GCUL: Ambiguity Identification in Text Emotion Classification via Cluster-Guided Learning

arXiv:2609.29327v1 Announce Type: cross Abstract: Selective classification enables a model to abstain from predictions on uncertain instances, but existing approaches typically reject them through con

Hardware

GHOST-Q: Towards Studying Grounding Hallucinations Overlooked Under Same-score TradeOffs in Quantized VLMS

arXiv:2609.29999v1 Announce Type: cross Abstract: Post-training quantization of vision--language models (VLMs) is typically assessed through aggregate task accuracy and memory savings, but preserving

hardwarearxiv-cs-ai

Graph, Loop, and Harness Engineering for Zero-Trust Agentic Data Engineering and Analytical Processing

arXiv:2609.29668v1 Announce Type: cross Abstract: Large language model agents increasingly automate data workflows, but end-to-end cloud data engineering and analytical execution require reliable coor

Tutorials

Guardrails or Roadblocks? Effects of Pedagogical Style and Context Awareness in AI Teaching Assistants for Programming

arXiv:2609.29995v1 Announce Type: cross Abstract: AI teaching assistants (AI TAs) backed by large language models (LLMs) and pedagogical guardrails are increasingly being integrated into programming c

tutorialsarxiv-cs-ai

Integrating Local Detail and Global Context: A Dual-Input Multi-Task Learning Framework for Bone Tumor Diagnosis

arXiv:2609.28732v1 Announce Type: cross Abstract: Primary bone tumors are rare but clinically aggressive neoplasms whose diagnosis from radiographs is challenged by heterogeneous morphology, subtle le

LabFactory: Building and Evaluating Executable AI Labs

arXiv:2609.28697v1 Announce Type: new Abstract: Scientific tasks specify a desired capability, but realizing it often requires building a computational system tailored to the task---acquiring data, de

agentsarxiv-cs-lg

Lightweight Vision Transformer-Based U-Net for Brain Tumor Segmentation from MRI

arXiv:2609.29785v1 Announce Type: new Abstract: Accurate brain tumor segmentation from Magnetic Resonance Imaging is essential for diagnosis, treatment planning, and surgical guidance. Although Convol

local-aiarxiv-cs-cv

MeshHeal: Two-Timescale Self-Healing for Gray Failures in Decentralized LLM Agent Networks

arXiv:2609.29015v1 Announce Type: new Abstract: Decentralized LLM-based multi-agent systems coordinate through local interactions, but an agent can remain responsive while its task-solving quality per