Search: “models”

REHEARSE: Experiential Rehearsal for Verbal Confidence Calibration in Large Language Models

arXiv:2508.14390v2 Announce Type: replace-cross Abstract: Large language models (LLMs) often express verbal confidence that is poorly aligned with actual correctness, limiting their reliability in saf

The Embedder's Dilemma: LLMs Are Better, but at What Cost?

DGX agent

arXiv:2608.12875v1 Announce Type: new Abstract: Should you replace your text-embedding pipeline with a large language model? We answer this with a controlled, cost-aware comparison of ten LLMs across

model-releasesarxiv-cs-cl

14 Aug 2026

UniTexture: Cross-Task Universal Adversarial Textures for Vision-Language-Action Models

arXiv:2608.13453v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models have emerged as generalist robotic policies capable of following diverse language instructions and performing a wi

Unlearning at Scale: State-Exact Trace-Preserving Deletion in Billion-Parameter Language Models

arXiv:2508.12220v2 Announce Type: replace-cross Abstract: Can a prospectively instrumented training continuation reproduce a deletion counterfactual exactly after selected examples leave its replay da

When Explanations Betray Backdoors: Black-Box Auditing for Language Model Classifiers

arXiv:2608.12623v1 Announce Type: new Abstract: Language model classifiers with explanations are used for moderation, routing, topic triage, and low-resource annotation. We study black-box auditing wh

researcharxiv-cs-cl

Z.ai debuts GLM-5.3 with long-horizon coding, cybersecurity upgrades

model-releasessiliconangle

Chinese artificial intelligence developer Z.ai Co. today debuted GLM-5.3, an open-source large language model that set records across several popular benchmarks. The LLM is based on an algorithm calle

A Theoretical Framework for Modular Learning of Robust Generative Models

arXiv:2602.17554v3 Announce Type: replace Abstract: Training large-scale generative models is resource-intensive and relies heavily on heuristic dataset weighting. We address two fundamental questions

applicationsarxiv-cs-lg

COLORA: Efficient Fine-Tuning for Convolutional Models with a Study Case on Optical Coherence Tomography Image Classification

arXiv:2505.18315v3 Announce Type: replace-cross Abstract: We introduce extbf{CoLoRA} (Convolutional Low-Rank Adaptation), a parameter-efficient fine-tuning method for convolutional neural networks (CN

Local Ai

Deep Activity Model: A Generative Approach for Human Mobility Pattern Synthesis

arXiv:2405.17468v3 Announce Type: replace-cross Abstract: Human mobility plays a crucial role in transportation, urban planning, and public health, but current approaches face important limitations. E

local-aiarxiv-cs-ai

Dual-Model Sentiment Analysis of Consumer Reviews in the Retail Coffee Sector Using Machine Learning and Deep Learning Approaches

arXiv:2608.12007v1 Announce Type: cross Abstract: Consumer reviews play an important role in shaping brand perception and business strategies, particularly in service-driven industries such as retail

applicationsarxiv-cs-ai

Foresight Without Seeing: Latent Futures for World Action Models

arXiv:2608.11605v1 Announce Type: new Abstract: World Action Models (WAMs) couple future visual prediction with robot action generation, enabling policies to model how the physical world evolves durin

Large Language Models Reproduce Racial Stereotypes When Used for Text Annotation

arXiv:2603.13891v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly used for automated text annotation in tasks ranging from academic research to content moderation

Motion-as-Prompt: Enhancing Motion Reasoning in Multimodal Large Language Models via Motion-Guided Cross-Frame Visual Prompting

arXiv:2608.11655v1 Announce Type: cross Abstract: Motion-centric video reasoning is fundamental to interactive applications such as robotic manipulation and autonomous navigation. However, multimodal

Ripple-Pivot Search: Active Parallel Decoding for Diffusion Large Language Models

arXiv:2608.11742v1 Announce Type: new Abstract: Diffusion Large Language Models (dLLMs) have emerged as a competitive alternative to autoregressive language models, offering the potential for substant

researcharxiv-cs-cl

Social Meaning in Large Language Models: Structure, Magnitude, and Pragmatic Prompting

arXiv:2604.02512v2 Announce Type: replace-cross Abstract: Large language models (LLMs) increasingly exhibit human-like patterns of pragmatic and social reasoning. This paper addresses two related ques

applicationsarxiv-cs-ai

Agents

Agentic AI infrastructure shifts enterprise focus from model choice to platform control

As agentic AI infrastructure moves from experimentation into production, enterprises are confronting a more complex question than which model to use: how to control the cost, data exposure and infrast

agentssiliconangle

An Exact Instrument for State Usage in Selective State-Space Models, and the Input-Driven Migration It Reveals

arXiv:2607.11796v2 Announce Type: replace Abstract: Selective state-space models such as Mamba route information through a bank of first-order modes whose input coupling is set by a learned selection

Cross-View Feature Matching: Survey, Benchmarking, and Foundation-Model Perspectives

arXiv:2608.11093v1 Announce Type: cross Abstract: Cross-view feature matching aims to establish reliable correspondences across images with large viewpoint variations. Over the past decade, the field

Decodable But Not Detachable: Training Data Granularity Determines Parametric Modularity in Large Language Models

arXiv:2608.10214v1 Announce Type: new Abstract: Do large language models contain domain-specific parametric shells: concentrated, causally necessary neuron populations whose removal selectively degrad

DEFT: Data-Efficient Frequency-domain Top-k Sampling via Inverse Discrete Fourier Transform for Spatiotemporal Dynamical Systems Modeling

arXiv:2608.11019v1 Announce Type: new Abstract: Modeling spatiotemporal dynamical systems governed by partial differential equations (PDEs) poses two major challenges: it either requires expensive phy

Energy and Performance Benchmarking of Deep Learning Models for Breast Cancer Detection

arXiv:2608.09996v1 Announce Type: cross Abstract: Recent advances in machine learning have greatly improved breast cancer detection, enabling more accurate and timely diagnosis. Deep learning (DL) mod

Evaluating Semantic and Spatial Guidance for Foundation Model Segmentation of Small-Scale PV in Remote Sensing Imagery

arXiv:2608.10801v1 Announce Type: new Abstract: Spatio-temporal PV data are essential for understanding adoption processes in off-grid regions, yet such data remain largely unavailable. Automated segm

Hardware

Ex-Omni-2D: Expressive Omni-Modal Dialogue Models with Native Visual Presence

arXiv:2608.10720v1 Announce Type: new Abstract: Omni-modal dialogue models can understand multimodal inputs and synthesize spoken replies, yet their responses remain visually disembodied. We introduce

hardwarearxiv-cs-ai

Foundation Model-Enabled Efficient Data Sampling (FEEDS): A label-efficient training strategy for pan-cancer, multi-tracer PET/CT datasets

arXiv:2608.11076v1 Announce Type: new Abstract: Automated lesion segmentation in whole-body PET/CT imaging can assist clinicians with cancer detection, staging, and treatment planning across radiotrac

INSIDE the Student's Mind: Jointly Modeling Latent Reasoning and Action in LLM Student Simulators

arXiv:2608.10492v1 Announce Type: new Abstract: Large Language Model (LLM)-based simulators often reproduce observable actions but fail to capture the underlying reasoning behind them. In education, w

MazzikaAI: A knowledge-based performance-to-prompt compiler for real-time Arabic maqam accompaniment with a streaming text-to-music model

arXiv:2608.10360v1 Announce Type: cross Abstract: Arabic maqam music microtonal, modal, and built on ornamented call and response is among the traditions most underserved by generative music models, w

applicationsarxiv-cs-ai

Physics-informed Diffusion Generative Model for Time-Series Data Synthesis in Dynamic Systems

arXiv:2608.10941v1 Announce Type: new Abstract: Industrial time-series signals, such as turbine temperature and rotational speed in aero-engines, are essential for monitoring the health and operationa

The Gaussian-Multinoulli Restricted Boltzmann Machine: A Potts Model Extension of the GRBM

arXiv:2505.11635v2 Announce Type: cross Abstract: Many real-world tasks, from associative memory to symbolic reasoning, benefit from discrete, structured representations that standard continuous laten

Local Ai

Toward the Cognitive--Physical Limits of Embodied Intelligence through a World-Model-Centric Autonomous Racing Agent

arXiv:2608.10618v1 Announce Type: new Abstract: Embodied artificial intelligence aims to develop agents that perceive, reason, and act through continuous interaction with the physical world. However,

local-aiarxiv-cs-ro

Towards Sustainable Artificial Intelligence: A Comprehensive Review and Comparative Analysis of Deep Learning Models' Carbon Footprint

arXiv:2608.09998v1 Announce Type: new Abstract: Artificial Intelligence (AI) and Machine Learning (ML) have become powerful tools for supporting and automating complex human tasks. Despite their benef

Agents

You chose the best model. Why is your agent still failing?

Public benchmarks can show how a model performs in general. Production reliability depends on the context and harness around it, which only your team can evaluate against its own data, workflows, and

agentsarize-ai

A foundation model of numerical intelligence with cross-disciplinary generalization

arXiv:2607.28432v2 Announce Type: replace Abstract: Intelligence is commonly understood as the ability to acquire and apply knowledge, adapt to unfamiliar situations and solve new problems. Large lang

An invertible generative model for forward and inverse problems

arXiv:2509.03910v2 Announce Type: replace-cross Abstract: We formulate inverse problems in a Bayesian framework and aim to train an invertible generative model that is capable of simulation (i.e., sam

Are Latent Reasoning Models Easily Interpretable?

arXiv:2604.04902v2 Announce Type: replace Abstract: Latent reasoning models (LRMs) have attracted significant research interest due to their low inference cost (relative to explicit reasoning models)

Diminishing Returns of Intelligence: The Non-Linear Relationship Between LLM Scale and User Perception in Short-Duration Open-Ended Social Human-Robot Interactions

model-releasesarxiv-cs-ro

arXiv:2608.08320v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly used to drive embodied social agents, yet it remains unclear whether larger models improve user perception

DoGMA: A Central-Dogma-Guided Foundation Model for Multi-Omics Alignment and Multi-Task Learning in Oncology

arXiv:2608.08148v1 Announce Type: cross Abstract: Attention mechanisms have been widely utilized in modern deep learning, and many existing multi-omics models inherit their conventional use to allow u

Emotion in an active inference model of human driving

arXiv:2608.07480v1 Announce Type: new Abstract: Active inference has emerged as a principled framework for modeling adaptive behavior by balancing goal-directed action with uncertainty reduction. It h

Ethical Framework for Responsible Foundational Models in Medical Imaging

arXiv:2406.11868v2 Announce Type: replace-cross Abstract: The emergence of foundational models represents a paradigm shift in medical imaging, offering extraordinary capabilities in disease detection,

Evolving Safety Landscape of Multi-modal Large Language Models: A Survey of Emerging Threats and Safeguards

arXiv:2608.07535v1 Announce Type: cross Abstract: Multi-modal large language models (MLLMs) integrate heterogeneous modalities through modality alignment and fusion, enabling stronger understanding an

HOPPER: Learnable Hop Extraction for Linearized Graph Sequence Models

model-releasesarxiv-cs-lg

arXiv:2608.09031v1 Announce Type: new Abstract: Graph neural networks typically propagate information through repeated message-passing layers, coupling the distance over which information travels with

Latent World Models with Monotone Planning Costs for Image-Goal Navigation

arXiv:2608.09073v1 Announce Type: new Abstract: Image-goal navigation with latent world models requires not only accurate future prediction, but also a planning cost that reliably ranks candidate acti

applicationsarxiv-cs-ro

Tutorials

Leveraging generative models to assist Monte Carlo sampling

arXiv:2608.07648v1 Announce Type: cross Abstract: Sampling high-dimensional probability distributions is a central task in scientific computing, with applications ranging from Bayesian inference to st

tutorialsarxiv-cs-lg

Listen, See and Track: Spatio-Temporal Audio-Visual Sound Event Reasoning for Omni-Modal Language Models

arXiv:2608.09435v1 Announce Type: new Abstract: Understanding dynamic sound sources requires jointly determining what produces a sound, where the source is located, and how it moves over time. Yet exi

LLMs Remember First, Forget Last: Dual-Process Interference in Large Language Models

arXiv:2603.00270v3 Announce Type: replace-cross Abstract: Large language models can process millions of tokens, yet how they handle conflicting information within context remains poorly understood. Fr

LookME: Lookup-Based Multimodal Embeddings for Layer Injection in Vision-Language Models

arXiv:2607.16305v2 Announce Type: replace-cross Abstract: Vision-Language Models (VLMs) have achieved strong progress in multimodal understanding. However, scaling dense or sparse Mixture-of-Experts (

Tutorials

MaxModShift: Model Privacy via Designed Shifts

arXiv:2608.09328v1 Announce Type: new Abstract: Model learning by an eavesdropper is treated as an estimation problem in a federated environment. The Fisher Information Matrix for the eavesdropper's e

tutorialsarxiv-cs-lg

Multilingual Agent-Based World Modeling for Social Science

arXiv:2512.07195v2 Announce Type: replace-cross Abstract: Multi-agent role-playing has recently shown promise for studying social behavior with language agents, but existing simulations are mostly mon

One Model to Magnify Them All: Efficient Scale-Invariant Histopathology via Conditional Normalization and Continuous Magnification Training

arXiv:2608.09403v1 Announce Type: new Abstract: Whole slide images (WSIs) in digital histopathology are acquired at discrete magnification levels encoding complementary diagnostic information from glo