Search: “models”

FIRE: Failure-Informed Runtime Engineering for Reliable Language-Model Agents

arXiv:2609.26048v1 Announce Type: cross Abstract: Language-model agents often reach a working solution and then fail to consistently deliver it. We study runtime policies: targeted natural-language in

23 Sept 2026

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Model Releases

Measuring the Serving Stack Instead of the Model: Hidden Confounds in Local Tool-Use Evaluation

DGX agent

arXiv:2609.26693v1 Announce Type: new Abstract: A coding agent must emit a valid tool call--a parseable invocation of a tool in the provided schema--before the harness can execute its chosen action. W

model-releasesarxiv-cs-cl

23 Sept 2026

Probabilistic Modeling of Jailbreak on Multimodal LLMs: From Quantification to Application

model-releasesarxiv-cs-cv

arXiv:2503.06989v5 Announce Type: replace-cross Abstract: Recently, Multimodal Large Language Models (MLLMs) have demonstrated their superior ability in understanding multimodal content. However, they

23 Sept 2026

Acceptance-Aware Draft Model Training for Speculative Decoding

arXiv:2609.24150v1 Announce Type: new Abstract: Speculative decoding accelerates large language model (LLM) inference by using a lightweight draft model to generate multiple candidate tokens that are

researcharxiv-cs-lg

Hardware

AgentRouter: Heterogeneous Model Routing for Cost-Optimal Multi-Step Agentic Workflows

arXiv:2609.22951v1 Announce Type: cross Abstract: Enterprise agentic systems that route every trajectory step to a frontier model waste 60-80% of their inference budget on subtasks that smaller models

hardwarearxiv-cs-cl

AR-WAM: A Visual-Conditioned Agent-Ready World Action Model for Robotic Manipulation

model-releasesarxiv-cs-ro

arXiv:2609.23578v1 Announce Type: new Abstract: As AI agents become increasingly capable, agent-driven robotic control is emerging as a compelling paradigm. However, prevailing vision-language-action

Moonworks Lunara: Modeling Artistic Intelligence

model-releasesarxiv-cs-cv

arXiv:2609.22272v1 Announce Type: new Abstract: We formulate Artistic Intelligence as exploration driven world realization, leaving space for creative possibility while preserving the semantic, artist

Multiple latent orderings better predict language model preferences

arXiv:2609.22170v1 Announce Type: cross Abstract: Language models are frequently employed in settings where they are asked to make value judgments and choices. These observed choices often exhibit int

Team DArgk at the 2026 ELOQUENT lab for evaluating generative language model quality: Residuals of Humanity: AI Detection Evasion via GRPO Fine-Tuning

arXiv:2609.22221v1 Announce Type: new Abstract: Large language models (LLMs) can generate fluent and coherent text that is increasingly difficult to distinguish from human writing, motivating the deve

A Scene Language Model for Open-Vocabulary Scene Mapping

model-releasesarxiv-cs-cv

arXiv:2609.21400v1 Announce Type: new Abstract: Open-vocabulary 3D scene mapping aims to build a persistent representation of the objects in an environment. Existing systems typically rely on engineer

21 Sept 2026

Local Ai

World Modeling in Transformers

arXiv:2609.21748v1 Announce Type: new Abstract: Behavioral failures can make a transformer appear to lack a world model even when it has learned faithful representations of its environment. We demonst

local-aiarxiv-cs-ai

21 Sept 2026

Hardware

Astronex-World 1.0: Real-Time Interactive World Model Foundation

arXiv:2609.20034v1 Announce Type: cross Abstract: We present Astronex-World 1.0, an open controllable video world-model foundation. Given a text prompt (text-to-video) or an initial observation (image

hardwarearxiv-cs-ai

Design of the IBM Granite 5.0 TurboCTC ASR Model

arXiv:2609.20104v1 Announce Type: new Abstract: We describe the architecture, training methodology and inference speedups of Granite 5.0 Turbo CTC, a 470 million parameter encoder-only model with an e

To Copy or Not to Copy: Controlling Speculative Decoding via Intrinsic Model Signals

arXiv:2609.20186v1 Announce Type: new Abstract: Speculative Decoding (SD) has significantly accelerated Large Language Model (LLM) inference, yet existing approaches face a fundamental tradeoff betwee

Zarya: A Hybrid Autoregressive--Masked Diffusion Language Model with Flexible Training and Dual-Mode Inference

arXiv:2609.19868v1 Announce Type: cross Abstract: Autoregressive language models (ARMs) are constrained by sequential, left-to-right generation, while masked diffusion models (MDMs) enable parallel de

A Calibrated Instrument for Measuring How Inference Optimizations Affect Output Quality

arXiv:2609.18005v1 Announce Type: new Abstract: Large language model optimization is an active research area, spanning quantization of model weights, early-exit methods for skipping layers, and specul

CPR: Combining global composing, local performing and full-sequence refining in piano rendering with continuous autoregressive modelling

arXiv:2609.18216v1 Announce Type: cross Abstract: Prompt-conditioned piano MIDI-to-Music rendering aims to faithfully render target notes while reproducing the timbre of a reference recording. Existin

safetyarxiv-cs-ai

Multimodal Behavior Tree Generation: A Small Vision-Language Model for Robot Task Planning

model-releasesarxiv-cs-ro

arXiv:2603.06084v2 Announce Type: replace Abstract: Large language models have been widely used for robotic task planning, often taking advantage of representations such as Behavior Trees (BTs). Visio

Pay Only for Disagreement: Certified No-Regression Verdicts for Model Updates with Matching Label-Complexity Bounds

arXiv:2609.17560v1 Announce Type: cross Abstract: Every production model is updated, by retraining, fine-tuning, quantization, or a silent vendor swap, and each update risks being worse than what it r

applicationsarxiv-cs-ai

Preventing Model Collapse: A Fisher-Rao Perspective on the Dynamics of Training with Synthetic Data

arXiv:2609.18878v1 Announce Type: new Abstract: Large Language Models (LLMs) are now routinely trained using synthetic data, since high-quality human data has been exhausted by the ever increasing nee

researcharxiv-cs-lg

WaveTLM: Reliable Time-Series Language Modeling through Task Compilation

model-releasesarxiv-cs-lg

arXiv:2609.18812v1 Announce Type: new Abstract: Time-series language models provide a shared natural-language interface across temporal tasks, but plausible text does not guarantee reliable task outpu

Can LLMs Model Incorrect Student Reasoning? A Case Study on Distractor Generation

arXiv:2603.15547v2 Announce Type: replace-cross Abstract: Modeling student misconceptions in a realistic manner is critical for AI in education. In this work, we examine how large language models (LLM

safetyarxiv-cs-ai

LimiX-2: A Contextual Mechanism Network Towards General Structured-Data Intelligence

arXiv:2609.17488v1 Announce Type: new Abstract: We introduce LimiX-2, a new model in the LimiX family, developed through model and data scaling guided by our previously established scaling laws. LimiX

PARSA-Bench: A Comprehensive Persian Audio-Language Model Benchmark

arXiv:2603.14456v2 Announce Type: replace Abstract: Persian poses unique audio understanding challenges through its classical poetry, traditional music, and pervasive code-switching, none of which is

Repurposing Deep Limit Order Book Forecasting for Scenario-Conditioned Market Impact Modeling

arXiv:2609.16930v1 Announce Type: cross Abstract: Deep Limit Order Book forecasting models capture nonlinear market dynamics, but their ability to quantify the effects of counterfactual order book mes

SOTER: A Generative Time-Series Foundation Model for Wearable Human Physiological Signals

arXiv:2609.16804v1 Announce Type: cross Abstract: Time-series foundation models have demonstrated strong cross-domain transfer, yet their common architectural assumptions remain poorly aligned with we

Another Blueprint In The Wall: How to Ask Frontier AI Like a Kid?

arXiv:2609.14803v1 Announce Type: new Abstract: This paper reports experiments across six frontier model types from OpenAI, Anthropic, xAI, and Google DeepMind. Ten independent sessions per model type

Hindsight Bias in Clinical Temporal Reasoning: How Future Data Exposure Affects Large Language Model Judgment

arXiv:2609.13454v1 Announce Type: cross Abstract: Clinical decisions are prospective, but clinical language models are often evaluated on retrospective records that reveal the final diagnosis, treatme

How User-AI Mistreatment Occurs and Matters in Conversational Systems?

arXiv:2609.13579v1 Announce Type: new Abstract: Safety research often focuses on model-generated harms, but users may also direct hostility, coercion, and adversarial pressure at models. Understanding

safetyarxiv-cs-ai

The Universe of Universes: Benefit Yield Functions, Implosion Thresholds, and Infrastructure-Aware Optimization in Multi-LLM Systems

arXiv:2609.15314v1 Announce Type: cross Abstract: We introduce the Universe of Universes (UoU) framework, which treats the full ecosystem of major large language models (LLMs) as a structured retrieva

Learning Sparse Latent Predictive Foundation Model for Multimodal Neuroimaging

arXiv:2606.14957v4 Announce Type: replace Abstract: Brain MRIs are routinely acquired as multiple complementary sequences with unique contrast weighting, including T1-weighed imaging (T1w) anatomic an

researcharxiv-cs-cv

14 Sept 2026

Self-supervised Pre-training Helps Retinal Disease Progression Modelling Most When Data Is Scarce

arXiv:2609.12834v1 Announce Type: new Abstract: Modelling how a disease progresses over time requires longitudinal imaging cohorts, which are scarce and small, whereas cross-sectional data -- one imag

researcharxiv-cs-cv

14 Sept 2026

Reference-Based Bias Detection in LLMs via Relative Representations of Hidden States

arXiv:2609.10060v1 Announce Type: new Abstract: Existing bias auditing methods typically rely on model outputs, requiring costly benchmarks or judge models and potentially missing internal shifts that

11 Sept 2026

TransClean: A Benchmark for Detecting and Extracting Clean Translations from Large Language Model Outputs

arXiv:2609.11399v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used for machine translation, yet their outputs often contain additional text beyond the translation itsel

11 Sept 2026

Behavioral Grammar: Detecting Adaptive Malware via Tiny Language Model Priors and Second-Order Temporal Analysis

arXiv:2608.00745v2 Announce Type: replace Abstract: Modern endpoint detection systems face a fundamental tension: signature-based approaches are trivially evaded by polymorphic or adaptive threats, wh

Evaluating Model Retraining under Drift: Paired Comparisons of Cumulative Subgroup Disparity

arXiv:2609.09788v1 Announce Type: new Abstract: Choosing when to retrain a deployed classifier requires assessing subgroup error rates across the sequence of models used, including periods between upd

safetyarxiv-cs-lg

SequenceO1: End-to-End Ultra-Long (100K) Sequence Modeling in Recommendation with Low-Rank Caching

arXiv:2609.08443v1 Announce Type: cross Abstract: Modeling long-term user behavior is central to sequential recommendation and billion-scale industrial recommender systems, yet production ranking mode

applicationsarxiv-cs-ai

Understanding the Impact of Model Pruning on Long-Tail Forgetting and Explanation Reliability in Medical Imaging

arXiv:2609.07803v1 Announce Type: new Abstract: Model pruning is widely used to compress deep neural networks, reducing memory and computational requirements with minimal impact on aggregate performan

Why Do LLM Agents Fail in Exploring New Environments? A World-Modeling Perspective

arXiv:2510.15047v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) as agents often fail to improve in new environments. We identify and characterize a failure mode we call explorat

Tutorials

BaNEL: Exploration Posteriors for Generative Modeling Using Only Negative Rewards

arXiv:2510.09596v2 Announce Type: replace Abstract: Today's generative models thrive with large amounts of supervised data and informative reward functions characterizing the quality of the generation

tutorialsarxiv-cs-lg

Cadence: Error-Bounded Lossy Compression of Demand Time Series with a Time-Series Foundation Model

model-releasesarxiv-cs-lg

arXiv:2609.06008v1 Announce Type: cross Abstract: We present Cadence, an error-bounded lossy compressor for numeric time series pairing a 330M-parameter time-series foundation model (Google TimesFM-3)

Agents

Hi-FLoop: Hierarchical State-Feedback Loops for Multi-Timescale World Modeling

arXiv:2609.08796v1 Announce Type: new Abstract: Multi-agent traffic simulation seeks diverse, coordinated, and physically realistic futures from maps and observed history. Long-horizon closed-loop gen

agentsarxiv-cs-cv

Instance-wise Linearization of Neural Network for Model Interpretation

arXiv:2310.16295v2 Announce Type: replace-cross Abstract: Neural network have achieved remarkable successes in many scientific fields. However, the interpretability of the neural network model is stil

applicationsarxiv-cs-cv

PAN: A World Model for General, Actionable, and Long-Horizon World Simulation

arXiv:2511.09057v4 Announce Type: replace Abstract: A world model is a cognitive simulator of the real-world environment allowing biological agents to reason about how the world evolves, whether spont

applicationsarxiv-cs-cv

Local Ai

PhysReal: Learning Real-World Deformable Object Physics via Hybrid Constitutive Modeling

arXiv:2609.07532v1 Announce Type: new Abstract: Learning physically plausible dynamics from visual observations is essential for interactive world models and embodied agents. However, modeling real-wo

local-aiarxiv-cs-ro

One Diffusion Model, Two Roles: Guided Trajectory Planning and Safety-Critical Scenario Generation in Closed-Loop Simulation

arXiv:2609.04921v1 Announce Type: cross Abstract: Diffusion probabilistic models can capture the multi-modal, interaction-rich distribution of joint future trajectories in driving scenes. We show that

7 Sept 2026

CROCODIL: Cross-Model Code Editing with LLMs

arXiv:2609.03894v1 Announce Type: new Abstract: Large language models (LLMs) have become ubiquitous tools for code generation and editing. However, development teams often use multiple LLM assistants.

4 Sept 2026

The Dice Roll Method: A Standardized Protocol for Repeated-Query Auditing of Large Language Model Brand Recommendations

arXiv:2609.04047v1 Announce Type: cross Abstract: Background: Researchers increasingly use repeated identical prompts to audit stochastic variation in large language model (LLM) brand recommendations,