Search: “models”

Slow Decay and Silenced Expression: Iterated Subliminal Trait Transfer in Language-Model Lineages

arXiv:2609.25721v1 Announce Type: cross Abstract: Language models are increasingly trained on the outputs of other models, forming chains that we call lineages, in which a trait present in one generat

researcharxiv-cs-cl

23 Sept 2026

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Model Releases

Training a Language Model End-to-End in Rust: An Experience Report

DGX agent

arXiv:2609.25008v1 Announce Type: new Abstract: I pretrained a language model end-to-end in Rust - alone, with no team, no PyTorch, and no Python in the training path - for $164 in rented GPU time. I

model-releasesarxiv-cs-cl

23 Sept 2026

A Hybrid Attention Model Learning Unified Time-aware Patch Representation for Irregular Multivariate Time Series Forecasting

arXiv:2609.22836v1 Announce Type: new Abstract: Time series foundation models (TSFMs) have recently delivered impressive zero-shot performance across diverse forecasting tasks. However, real-world dec

DexTacWAM: A Visuo-Tactile World-Action Model for Dexterous Manipulation

arXiv:2609.24976v1 Announce Type: cross Abstract: Dexterous manipulation depends on contact dynamics that are often only partially observable from vision. Recent World-Action Models (WAMs) couple pred

researcharxiv-cs-cv

Generalized Multimodal Foundation Model

arXiv:2609.22107v1 Announce Type: cross Abstract: Making prediction with multimodal data is widely used in diverse scenarios. Existing multimodal fusion models, once deployed, can only handle predefin

applicationsarxiv-cs-cl

Vision2CAD: A Visual Agent Harness for Explicit Geometry Referencing and Localization in Parametric CAD Modeling

arXiv:2609.22688v1 Announce Type: new Abstract: Generating parametric CAD models requires accurate geometry and stable feature dependencies. Existing methods face challenges in selecting geometric ref

Message capacity and claim wording set the transition points of collective truth-finding in language-model networks

arXiv:2609.19183v1 Announce Type: cross Abstract: Whether human or large language model (LLM), an agent in a discussion reads only a few of the others' contributions, bounded by cognition, context, or

18 Sept 2026

Code Consistency Preference Optimization Verification for Language Model Alignment

arXiv:2609.19002v1 Announce Type: cross Abstract: Execution-based verification enhances large language models' mathematical reasoning through computational soundness and dependency-aware filtering. Ho

17 Sept 2026

Function Lives Where Variance Doesn't: Task-Weighted Charts of a Language Model's Computation

arXiv:2609.18989v1 Announce Type: new Abstract: How many dimensions does a language model's computation actually use? The question is ill-posed until one names a functional. Task-weighted charts make

17 Sept 2026

AllShowers: One model for all calorimeter showers

arXiv:2601.11716v2 Announce Type: replace-cross Abstract: Accurate and efficient detector simulation is essential for modern collider experiments. To reduce the high computational cost, various fast m

safetyarxiv-cs-lg

An Empirical Study of Counterfactual Self-Explanations in LLMs

arXiv:2609.17119v1 Announce Type: new Abstract: Large language models can easily generate explanations for their own outputs, but such self-explanations are not necessarily faithful to the model's beh

Hardware

FlashVector: Agent for Hierarchical Model Serving Stack Optimization

arXiv:2609.17391v1 Announce Type: new Abstract: Model serving is one of the largest cost drivers in production recommender systems. Maximizing its throughput requires navigating a deeply layered hiera

hardwarearxiv-cs-ai

POSPAN: Position-Constrained Span Masking for Language Model Pre-training

arXiv:2609.16061v1 Announce Type: cross Abstract: Span-level masked language modeling (MLM) has shown to be advantageous to pre-trained language models over the original single-token MLM, as entities/

A Language-Guided Multimodal Foundation Model for Zero-Shot and Multi-Task Brain Signal Analysis

arXiv:2609.15740v1 Announce Type: cross Abstract: Brain signal analysis is essential for both neuroscience research and clinical diagnostics, yet current approaches face critical limitations. End-to-e

safetyarxiv-cs-ai

BudgetBench: A Budget-Tiered Protocol and Pilot Harness for Memory Strategy Evaluation in Local Large Language Model Agents

arXiv:2609.13149v1 Announce Type: cross Abstract: For local large language model agents, active context is a scarce resource: memory capacity, prefill latency, cache growth, and service objectives all

Is my model perplexed for the right reason? Contrasting LLMs' Benchmark Behavior with Token-Level Perplexity

arXiv:2603.29396v2 Announce Type: replace Abstract: Standard evaluations of Large language models (LLMs) focus on task performance, offering limited insight into whether correct behavior reflects appr

PRISM-UDE: Physics-Regularized Iterative Symbolic Modeling of 3nm FinFETs via Universal Differential Equation

arXiv:2609.13200v1 Announce Type: cross Abstract: Compact transistor models are the mathematical backbone of circuit simulation. However, at advanced nodes such as 3nm, transport physics becomes too c

YOLO12-MambaScan: An Efficient Object Detector with High-Frequency Enhancement and State-Space Modeling

arXiv:2609.13647v1 Announce Type: new Abstract: The rapid development of unmanned aerial vehicle (UAV) technology has made aerial-image object detection increasingly important for natural-resource mon

Efficient Vision-Language-Action Management and Serving for Robot Factories

arXiv:2609.12075v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models show high robotic manipulation capabilities via a two-stage design: a Vision-Language Model (VLM) stage followed b

safetyarxiv-cs-lg

14 Sept 2026

Continuous-Time Acoustic Modelling with Neural Controlled Differential Equations

arXiv:2609.11725v1 Announce Type: cross Abstract: Text-to-speech (TTS) models commonly address text--speech alignment by expanding phone-level encoder states to frame-level decoder inputs using predic

safetyarxiv-cs-ai

12 Sept 2026

Beyond Top Words: MonoTM for Topic Modeling with Interpretable Monosemantic Features

arXiv:2609.09575v1 Announce Type: new Abstract: Topic models summarize large text corpora, but top-ranked words often provide only a limited representation of topic semantics. Sparse autoencoders (SAE

Cross-Model Agreement as a Deployment-Time Reliability Signal for Automatic Polyp Segmentation

arXiv:2609.10495v1 Announce Type: new Abstract: In real-time colonoscopy, ground-truth annotations are unavailable at inference, so polyp segmentation models can fail silently. We propose Referee-Base

HaWMPO: Hallucination-Aware World Model-based Policy Optimization for Generalist Robot Policy

model-releasesarxiv-cs-ro

arXiv:2609.09941v1 Announce Type: new Abstract: Generalist robot policies have demonstrated strong generalization across robotic manipulation tasks, yet their success rates remain limited in com- plex

LANTERN: Language Model Assessment on Noisy and Transformed Tasks for Understanding Error and Robustness Nuances

arXiv:2609.07309v1 Announce Type: cross Abstract: Robustness evaluation of large language models (LLMs) remains a critical challenge, particularly in assessing their sensitivity to perturbations in in

Recovering Temporal and Geographic Signals from Language Model Embeddings

arXiv:2609.05721v1 Announce Type: new Abstract: Understanding whether language-model embeddings encode structured real-world information is important for both representation analysis and information r

applicationsarxiv-cs-ai

RiLM: Parameter-Efficient Language Modeling via Geodesic Decoding

arXiv:2609.10305v1 Announce Type: new Abstract: Language models under one million parameters matter for edge deployment, domain adaptation, and reproducible research, yet a two-layer LSTM or Transform

Ambient @ EgoLongQA 2026: Distilling Long-Video perception into a Sub-2B Model

arXiv:2609.07154v1 Announce Type: new Abstract: We describe our entry to the EgoLongQA track of the Wearable-AI Challenge in ECCV 2026, which placed first in the <=2B parameter division with 0.8279 on

Assessing Covariate-Informed Grid Load Forecasting with a Time-Series Foundation Model

arXiv:2609.06656v1 Announce Type: new Abstract: Modern power systems are growing increasingly complex as they integrate diverse generation sources to meet rising demand, making accurate load forecasti

Local Ai

Broken on Arrival: Silently Defective LLM Artifacts in Public Model Registries and How to Catch Them

arXiv:2609.05881v1 Announce Type: cross Abstract: Developers increasingly run large language models locally by pulling quantized GGUF artifacts from public registries, yet nothing in the distribution

local-aiarxiv-cs-lg

CST-WM: A Causally Structured World Model for Embodied Visual Tracking

arXiv:2609.06302v1 Announce Type: new Abstract: Embodied visual tracking requires a robot not only to react to the current view, but to choose actions that preserve or recover future evidence of a mov

safetyarxiv-cs-cv

Agents

TrojanWorld: Backdooring World-Model Agents via Imagination Steering

arXiv:2609.07051v1 Announce Type: new Abstract: World models increasingly serve as the predictive core of model-based reinforcement learning agents, enabling them to simulate future dynamics and reaso

agentsarxiv-cs-lg

Uncertainty Is Not a Safety Net for Clinical VQA, but Can It Anticipate Model Failure?

arXiv:2606.16583v2 Announce Type: replace Abstract: Safe deployment of clinical vision-language models (VLMs) requires reliable uncertainty estimation (UE): a signal indicating when predictions should

safetyarxiv-cs-cl

4 Sept 2026

Local Ai

Random Forest-Informed Cellular Automaton for Large-Scale Wildfire Spread Modelling

arXiv:2609.01675v1 Announce Type: cross Abstract: Accurate large-scale wildfire spread modelling requires models that capture both the environmental conditions associated with fire occurrence and the

local-aiarxiv-cs-lg

3 Sept 2026

Hardware

CacheBridge: Efficient Cross-Model KV Cache Transfer

arXiv:2609.00891v1 Announce Type: new Abstract: Sharing context between LLMs in a multi-model system requires the receiving model to prefill the shared prefix because KV caches are model-specific. Rec

hardwarearxiv-cs-ai

2 Sept 2026

Toppling the Hierarchy in Byte-level Language Modeling

arXiv:2609.00463v1 Announce Type: new Abstract: This work examines recent byte-level models and their failure to perfectly manipulate characters. State-of-the-art byte-level models use a hierarchical

researcharxiv-cs-cl

2 Sept 2026

Variance-Adaptive Muon: Pre-Orthogonalization Variance Modulation for Efficient Language Model Pretraining

arXiv:2601.14603v2 Announce Type: replace Abstract: Optimizer design plays a central role in efficient language model pretraining, directly affecting optimization dynamics, convergence speed, and comp

2 Sept 2026

A Unifying Perspective on Language Model Representations: From Filler-Role Structure to Mechanistic Interpretability

arXiv:2608.29034v1 Announce Type: cross Abstract: A wide range of methods have been proposed for interpreting language models, delivering important insights into their inner workings. However, differe

1 Sept 2026

One Capability or Many? Testing the Economic Validity of Frontier AI Evaluation

arXiv:2608.29420v1 Announce Type: new Abstract: Frontier-model leaderboards now rank systems based on economic benchmarks, tests of how well models carry out professional tasks from software engineeri

1 Sept 2026

Standardizing Longitudinal Radiology Report Evaluation via Large Language Model Annotation

model-releasesarxiv-cs-ai

arXiv:2601.16753v2 Announce Type: replace-cross Abstract: Longitudinal information in radiology reports refers to the sequential tracking of findings across multiple examinations over time, which is c

1 Sept 2026

PersonaEdit: Representative Sample Selection for Personalized Model Editing

arXiv:2608.27816v1 Announce Type: new Abstract: Personalization has attracted growing interest in LLM applications, yet existing retrieval-based approaches depend heavily on retrieval quality and degr

researcharxiv-cs-cl

31 Aug 2026

Anatomy-Guided Foundation Model Adaptation with Within-Case Prototype Supervision for Standard Plane Detection in Fetal Ultrasound Blind Sweeps

arXiv:2608.27051v1 Announce Type: new Abstract: Detecting the fetal abdominal circumference standard plane in low-cost obstetric blind sweeps is a highly imbalanced frame-classification problem: posit

HALO: A Heterogeneity-Aware Language-Aligned IMU Foundation Model for Open-Set Human Activity Recognition

arXiv:2608.27233v1 Announce Type: new Abstract: Human Activity Recognition (HAR) using inertial measurement units (IMUs) enables a wide range of applications, yet the field still lacks a unified model

applicationsarxiv-cs-lg

Puro-2B: Poor Lab's Qwen2-1.5B Trained on RTX 5090 within $5090

arXiv:2608.27370v1 Announce Type: new Abstract: Language model pretraining has become almost synonymous with prohibitive cost, placing it out of reach for much of the academic and open-source communit

Robust Neural Stimulation Response Modeling Through Meta-Learning and Pretraining

arXiv:2608.26649v1 Announce Type: new Abstract: Objective: Model-based closed-loop neural stimulation holds promise for therapeutic applications ranging from Parkinson's disease to sensory restoration

researcharxiv-cs-lg

Finding and using interpretable latents in a neutrino foundation model with sparse autoencoders

arXiv:2608.26090v1 Announce Type: cross Abstract: We present a first application of sparse-autoencoder-based mechanistic interpretability to particle physics. Studying a neutrino foundation model pret

researcharxiv-cs-lg

27 Aug 2026

Local Ai

Planetary Prediction Engine: Autonomous Geospatial Prediction via Intelligent Data Selection and Foundation Model Embeddings

arXiv:2608.26088v1 Announce Type: cross Abstract: Addressing critical global challenges, from food security and disaster risk to disease outbreaks and socio-economic vulnerability, demands high-fideli

local-aiarxiv-cs-lg

27 Aug 2026

Data Mixing as Mixture Experiment: Response Surface Methodology and Optimal Design for Large Language Model Pretraining

arXiv:2608.23922v1 Announce Type: new Abstract: Data mixing is a central design problem in large language model pretraining: given a fixed token budget, practitioners must decide how much data to allo

applicationsarxiv-cs-ai

26 Aug 2026

Discovering Cross-Language Reasoning Invariance in LLMs with Geometry-Invariant Sparse Autoencoders