Search: “models”

Information as Structural Alignment: A Dynamical Theory of Continual Learning

arXiv:2604.07108v1 Announce Type: cross Abstract: Catastrophic forgetting is not an engineering failure. It is a mathematical consequence of storing knowledge as global parameter superposition. Existi

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Initialisation Determines the Basin: Efficient Codebook Optimisation for Extreme LLM Quantization

DGX agent

arXiv:2604.08118v1 Announce Type: new Abstract: Additive quantization enables extreme LLM compression with O(1) lookup-table dequantization, making it attractive for edge deployment. Yet at 2-bit prec

model-releasesarxiv-cs-cl

10 Apr 2026

KV Cache Offloading for Context-Intensive Tasks

arXiv:2604.08426v1 Announce Type: cross Abstract: With the growing demand for long-context LLMs across a wide range of applications, the key-value (KV) cache has become a critical bottleneck for both

LiloDriver: A Lifelong Learning Framework for Closed-loop Motion Planning in Long-tail Autonomous Driving Scenarios

model-releasesarxiv-cs-ro

arXiv:2505.17209v2 Announce Type: replace Abstract: Recent advances in autonomous driving research towards motion planners that are robust, safe, and adaptive. However, existing rule-based and data-dr

LNN-PINN: A Unified Physics-Only Training Framework with Liquid Residual Blocks

model-releasesarxiv-cs-lg

arXiv:2508.08935v4 Announce Type: replace Abstract: Physics-informed neural networks (PINNs) have attracted considerable attention for their ability to integrate partial differential equation priors i

MARCH: Evaluating the Intersection of Ambiguity Interpretation and Multi-hop Inference

arXiv:2509.22750v3 Announce Type: replace Abstract: Real-world multi-hop QA is naturally linked with ambiguity, where a single query can trigger multiple reasoning paths that require independent resol

MedDialBench: Benchmarking LLM Diagnostic Robustness under Parametric Adversarial Patient Behaviors

arXiv:2604.06846v1 Announce Type: cross Abstract: Interactive medical dialogue benchmarks have shown that LLM diagnostic accuracy degrades significantly when interacting with non-cooperative patients,

MoE Routing Testbed: Studying Expert Specialization and Routing Behavior at Small Scale

arXiv:2604.07030v1 Announce Type: new Abstract: Sparse Mixture-of-Experts (MoE) architectures are increasingly popular for frontier large language models (LLM) but they introduce training challenges d

researcharxiv-cs-lg

Agents

MolmoWeb: Open Visual Web Agent and Open Data for the Open Web

arXiv:2604.08516v1 Announce Type: new Abstract: Web agents--autonomous systems that navigate and execute tasks on the web on behalf of users--have the potential to transform how people interact with t

agentsarxiv-cs-cv

Monocular Depth Estimation From the Perspective of Feature Restoration: A Diffusion Enhanced Depth Restoration Approach

arXiv:2604.07664v1 Announce Type: new Abstract: Monocular Depth Estimation (MDE) is a fundamental computer vision task with important applications in 3D vision. The current mainstream MDE methods empl

MonoUNet: A Robust Tiny Neural Network for Automated Knee Cartilage Segmentation on Point-of-Care Ultrasound Devices

arXiv:2604.07780v1 Announce Type: cross Abstract: Objective: To develop a robust and compact deep learning model for automated knee cartilage segmentation on point-of-care ultrasound (POCUS) devices.

safetyarxiv-cs-cv

MR-ImagenTime: Multi-Resolution Time Series Generation through Dual Image Representations

arXiv:2603.28253v2 Announce Type: replace-cross Abstract: Time series forecasting is vital across many domains, yet existing models struggle with fixed-length inputs and inadequate multi-scale modelin

applicationsarxiv-cs-ai

Multi-Turn Reasoning LLMs for Task Offloading in Mobile Edge Computing

arXiv:2604.07148v1 Announce Type: new Abstract: Emerging computation-intensive applications impose stringent latency requirements on resource-constrained mobile devices. Mobile Edge Computing (MEC) ad

safetyarxiv-cs-lg

On the Global Photometric Alignment for Low-Level Vision

arXiv:2604.08172v1 Announce Type: new Abstract: Supervised low-level vision models rely on pixel-wise losses against paired references, yet paired training sets exhibit per-pair photometric inconsiste

safetyarxiv-cs-cv

PrivFedTalk: Privacy-Aware Federated Diffusion with Identity-Stable Adapters for Personalized Talking-Head Generation

arXiv:2604.08037v1 Announce Type: cross Abstract: Talking-head generation has advanced rapidly with diffusion-based generative models, but training usually depends on centralized face-video and speech

Probabilistic Language Tries: A Unified Framework for Compression, Decision Policies, and Execution Reuse

arXiv:2604.06228v1 Announce Type: cross Abstract: We introduce probabilistic language tries (PLTs), a unified representation that makes explicit the prefix structure implicitly defined by any generati

safetyarxiv-cs-ai

PULSE: Privileged Knowledge Transfer from Rich to Deployable Sensors for Embodied Multi-Sensory Learning

arXiv:2510.24058v2 Announce Type: replace-cross Abstract: Multi-sensory systems for embodied intelligence, from wearable body-sensor networks to instrumented robotic platforms, routinely face a sensor

Quantitative Estimation of Target Task Performance from Unsupervised Pretext Task in Semi/Self-Supervised Learning

arXiv:2508.07299v2 Announce Type: replace-cross Abstract: The effectiveness of unlabeled data in Semi/Self-Supervised Learning (SSL) depends on appropriate assumptions for specific scenarios, thereby

Reasoning Within the Mind: Dynamic Multimodal Interleaving in Latent Space

arXiv:2512.12623v3 Announce Type: replace-cross Abstract: Recent advancements in Multimodal Large Language Models (MLLMs) have significantly enhanced cross-modal understanding and reasoning by incorpo

safetyarxiv-cs-cl

Reflection-Based Task Adaptation for Self-Improving VLA

arXiv:2510.12710v3 Announce Type: replace Abstract: Pre-trained Vision-Language-Action (VLA) models represent a major leap towards general-purpose robots, yet efficiently adapting them to novel, speci

safetyarxiv-cs-ro

Riemann-Bench: A Benchmark for Moonshot Mathematics

arXiv:2604.06802v1 Announce Type: new Abstract: Recent AI systems have achieved gold-medal-level performance on the International Mathematical Olympiad, demonstrating remarkable proficiency at competi

SciFigDetect: A Benchmark for AI-Generated Scientific Figure Detection

arXiv:2604.08211v1 Announce Type: new Abstract: Modern multimodal generators can now produce scientific figures at near-publishable quality, creating a new challenge for visual forensics and research

SE-Enhanced ViT and BiLSTM-Based Intrusion Detection for Secure IIoT and IoMT Environments

arXiv:2604.06254v1 Announce Type: cross Abstract: With the rapid growth of interconnected devices in Industrial and Medical Internet of Things (IIoT and MIoT) ecosystems, ensuring timely and accurate

Seeing but Not Thinking: Routing Distraction in Multimodal Mixture-of-Experts

arXiv:2604.08541v1 Announce Type: cross Abstract: Multimodal Mixture-of-Experts (MoE) models have achieved remarkable performance on vision-language tasks. However, we identify a puzzling phenomenon t

safetyarxiv-cs-cl

Stabilizing Unsupervised Self-Evolution of MLLMs via Continuous Softened Retracing reSampling

arXiv:2604.03647v2 Announce Type: replace-cross Abstract: In the unsupervised self-evolution of Multimodal Large Language Models, the quality of feedback signals during post-training is pivotal for st

researcharxiv-cs-ai

TeamLLM: A Human-Like Team-Oriented Collaboration Framework for Multi-Step Contextualized Tasks

arXiv:2604.06765v1 Announce Type: cross Abstract: Recently, multi-Large Language Model (LLM) frameworks have been proposed to solve contextualized tasks. However, these frameworks do not explicitly em

Understanding Structured Financial Data with LLMs: A Case Study on Fraud Detection

arXiv:2512.13040v2 Announce Type: replace-cross Abstract: Detecting fraud in financial transactions typically relies on tabular models that demand heavy feature engineering to handle high-dimensional

applicationsarxiv-cs-cl

Weakly-Supervised Lung Nodule Segmentation via Training-Free Guidance of 3D Rectified Flow

arXiv:2604.08313v1 Announce Type: new Abstract: Dense annotations, such as segmentation masks, are expensive and time-consuming to obtain, especially for 3D medical images where expert voxel-wise labe

researcharxiv-cs-cv

AdaR: A Framework for Equipping LLMs with Adaptive Reasoning

arXiv:2510.04617v3 Announce Type: replace Abstract: Mathematical reasoning is a primary indicator of large language models (LLMs) intelligence. However, existing LLMs exhibit failures in robustness an

researcharxiv-cs-ai

Adversarial Training Improves Generalization Under Distribution Shifts in Bird Sound Classification

model-releasesarxiv-cs-lg

arXiv:2507.13727v2 Announce Type: replace Abstract: Adversarial training is a promising strategy for enhancing robustness against adversarial attacks, but its impact on generalization under substantia

All four leading LLMs talk more than they listen to personality-verified synthetic help-seekers

arXiv:2608.22425v1 Announce Type: cross Abstract: Large language models are increasingly consulted at moments of distress, yet single-turn benchmarks neither test sustained exchanges nor distinguish b

researcharxiv-cs-cl

BenthicFlow: Generating Extensible Underwater Environments via Flow Matching

arXiv:2608.23173v1 Announce Type: new Abstract: Computer vision applications for 3D scene understanding in underwater environments remain challenging due to the lack of high-quality 3D data and the in

researcharxiv-cs-cv

Hardware

BIMScript: Material-Aware Structured Scene Programs for BIM Ingestion

arXiv:2608.21447v1 Announce Type: new Abstract: Structured-language models such as SceneScript reconstruct a scene as a short program of parametric commands, an inherently editable and semantically ex

hardwarearxiv-cs-cv

Local Ai

Breaking the Assumptions: Auditing Input-Side Jailbreak Defenses Against Semantic Attacks

arXiv:2608.21895v1 Announce Type: cross Abstract: Locally deployed Large Language Models (LLMs) via inference engines such as Ollama run without the moderation and abuse detection present in API-serve

local-aiarxiv-cs-ai

BulletTime: Decoupled Control of Time and Camera Pose for Video Generation

arXiv:2512.05076v2 Announce Type: replace Abstract: Emerging video diffusion models achieve high visual fidelity but fundamentally couple scene dynamics with camera motion, limiting their ability to p

applicationsarxiv-cs-cv

CALIBURN: Self-Calibrated LLM Unlearning Alignment

arXiv:2602.02824v2 Announce Type: replace Abstract: LLM unlearning aims to remove the influence of undesirable knowledge from pretrained language models, which offers a practical mechanism for address

safetyarxiv-cs-cl

Cross-validating causal discovery via Leave-One-Variable-Out

arXiv:2411.05625v2 Announce Type: replace-cross Abstract: We propose a new approach to falsify causal discovery algorithms without ground truth, which is based on testing the causal model on a variabl

researcharxiv-cs-lg

CRS-Bench: A Reference-Relative Reliability Benchmark for Medical Image Encoders

arXiv:2608.22059v1 Announce Type: cross Abstract: Pretrained image encoders are central to medical image classification, where expert annotation is costly and task-specific cohorts are often limited.

Data-Centric Benchmark for Label Noise Estimation and Ranking in Remote Sensing Binary Building Segmentation

arXiv:2603.00604v2 Announce Type: replace Abstract: High-quality pixel-level annotations are essential for the semantic segmentation of remote sensing imagery. However, such labels are expensive to ob

Definitional Sensitivity in Media Bias Detection: A Multi-Definition Dataset and Benchmark

arXiv:2608.23095v1 Announce Type: new Abstract: Media bias detection relies on definitions and examples that specify what counts as bias, yet these specifications often vary across datasets or remain

DelistBench: Evaluating Search-Enabled LLMs for Auditable Corporate-Event Database Completion

arXiv:2608.22770v1 Announce Type: new Abstract: Financial institutions need an independent way to detect missing, stale, and misclassified corporate-event records in vendor databases. We introduce Sea

Dissecting Neuro-Symbolic Quality Assurance for Synthetic Oncology Data Generation

arXiv:2608.22085v1 Announce Type: new Abstract: Synthetic clinical data generation with large language models addresses the scarcity that limits cancer staging research, but oncology hallucinations ar

researcharxiv-cs-ai

Enhancing Sim2Real Transfer for Torque-Controlled Robots through Real2Sim Dynamics Estimation and Reinforcement Learning

model-releasesarxiv-cs-ro

arXiv:2608.22629v1 Announce Type: new Abstract: Transferring reinforcement learning policies from simulation to Real-World robots remains a major challenge, particularly when dealing with low-level to

EvoWiki: Incremental State Overwriting and Traceable Question Answering for Cross-Meeting Knowledge Evolution

arXiv:2608.23265v1 Announce Type: new Abstract: In long-term collaboration spanning multiple meetings, factual states such as decisions and risks are continually revised, overturned, and replaced. Exi

Extending the Horizon of Early Diagnosis: Lung Cancer Prediction with Vision Transformers

arXiv:2608.21571v1 Announce Type: new Abstract: Lung cancer remains a leading cause of cancer-related mortality worldwide, and early diagnosis is critical for improving survival. However, early-stage

researcharxiv-cs-cv

Few-Shot Cross-Dataset Adaptation for Tuberculosis Detection Using DenseNet

arXiv:2608.21427v1 Announce Type: new Abstract: Tuberculosis (TB) is one of the most common and dangerous bacterial ailments. Every year, it causes a large number of deaths worldwide. Although many de

applicationsarxiv-cs-cv

FinixDoc: Rethinking Financial Document Parsing Beyond Saturated Benchmarks

arXiv:2608.22842v1 Announce Type: new Abstract: Financial document parsing requires accuracy, structural consistency, and verifiability that current benchmarks often fail to reflect. We present FinixD

Guidance for Prior Change via Density Ratio Estimation

model-releasesarxiv-cs-lg

arXiv:2608.21729v1 Announce Type: cross Abstract: Simulation-Based Inference (SBI) serves as a vital framework for parameter inference in scientific fields where simulators involve intractable likelih