Search: “models”

SpecBraM: What Should an EEG Foundation Model Predict? Masked Band-Power Prediction versus Waveform Reconstruction

arXiv:2610.07484v1 Announce Type: new Abstract: Self-supervised EEG models often reconstruct masked waveforms or predict discrete codes. We study a task-aligned alternative: masked band-power predicti

7 Oct 2026

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Research

KALEIDO: Input-Space Adaptation of a Vision Model for Time-Series Forecasting Through Gated Fold Geometries

DGX agent

arXiv:2610.04786v1 Announce Type: cross Abstract: Time-series foundation models buy zero-shot forecasting with large temporal corpora; a vision model needs none, since a natural image implicitly embed

researcharxiv-cs-cv

6 Oct 2026

Mind the Execution Gap: Action-Semantic Mismatch in World-Model Control

arXiv:2610.06582v1 Announce Type: cross Abstract: World-model controllers rely on action-conditioned dynamics for prediction and planning, yet real control systems often execute commands asynchronousl

Ultrasound Operator Guidance Using World Modeling and Retrieval Based Action Planning

arXiv:2610.06008v1 Announce Type: cross Abstract: Ultrasound is widely used, but acquisition quality is heavily dependent on the operator's knowledge and expertise. With demand for examinations outpac

tutorialsarxiv-cs-cv

Video2World: Benchmarking Coding Agents for Interactive World Modeling from Embodied Videos

arXiv:2610.04432v1 Announce Type: new Abstract: Building interactive simulators from real-world observations is a promising way to scale embodied data, but current pipelines still rely heavily on manu

When Does a Diffusion Model Decide What to Draw ?

arXiv:2610.05645v1 Announce Type: new Abstract: A diffusion model starts from pure noise and removes it step by step. Somewhere along the way it stops being able to become 'anything' and becomes commi

tutorialsarxiv-cs-lg

Context-Tower Conversion Preserves Generation While Freezing Retains Knowledge: Low-Budget AR-to-Diffusion Conversion of MoE LLMs

arXiv:2610.02657v1 Announce Type: new Abstract: Converting a pretrained autoregressive (AR) model to a diffusion language model (dLLM) enables parallel generation without pretraining a new model. Publ

Demystifying LLM-as-a-Judge: Analytically Tractable Model for Inference-Time Scaling

arXiv:2512.19905v3 Announce Type: replace-cross Abstract: Recent developments in large language models have shown advantages in reallocating a notable share of computational resource from training tim

researcharxiv-cs-ai

FALCON: A Model and Dataset Agnostic Framework for Synthetic Data Generation for NL2SQL Pairs

model-releasesarxiv-cs-cl

arXiv:2610.03625v1 Announce Type: new Abstract: Relational databases are among the most widely deployed forms of structured knowledge, and natural language access to them requires grounding language o

SoftGene: Protein Language Model-Enhanced Soft Prompting for Interpretable Gene Set Annotation

arXiv:2610.03029v1 Announce Type: new Abstract: Gene set analysis is a cornerstone of functional genomics, yet it remains labor-intensive and heavily dependent on manual curation and expert biological

VIGOR: Zero-Shot Visual Generalization via Latent-Space Consistency in Model-Based Reinforcement Learning

arXiv:2610.02801v1 Announce Type: new Abstract: Model-based reinforcement learning (MBRL) achieves strong sample efficiency by planning within learned latent dynamics, yet its performance degrades sub

researcharxiv-cs-ai

CHILLGuard: Towards Fine-Grained Chinese LLM Safety Guardrail with Scalable Data Construction and Model-aware Preference Alignment

arXiv:2606.15396v2 Announce Type: replace-cross Abstract: Malicious content generated from large language models (LLMs) could pose severe safety risks and ethical concerns. While existing LLM safety g

2 Oct 2026

Efficient Generative Modeling beyond Memoryless Diffusion via Adjoint Schrodinger Bridge Matching

arXiv:2602.15396v2 Announce Type: replace Abstract: Diffusion models often yield highly curved trajectories and noisy score targets due to an uninformative, memoryless forward process that induces ind

tutorialsarxiv-cs-cv

2 Oct 2026

Measuring the Microtask Eligibility Gap: When Is an Off-the-Shelf SLM Enough for an Agent Harness?

arXiv:2610.00025v1 Announce Type: new Abstract: Agent harnesses increasingly want to run small language models (SLMs) on the microtasks around a frontier large language model (LLM) planner: auto-appro

2 Oct 2026

A Generalisation Signal Need Not Be a Model-Selection Signal

arXiv:2609.39099v1 Announce Type: cross Abstract: Model selection in computational biology often relies on validation data drawn from the training regime, even when deployment lies outside it. When va

researcharxiv-cs-ai

CellMSA: Context Modeling for Single-Cell Representation Learning

arXiv:2609.38908v1 Announce Type: cross Abstract: Single-cell transcriptomics enables profiling of cellular states at unprecedented resolution, but its high dimensionality, sparsity, and technical bat

safetyarxiv-cs-ai

Dream4ACT: A Shared Visual Action Interface for Multi-Embodiment Video-Action Modeling

arXiv:2609.40153v1 Announce Type: new Abstract: Video generation models (VGMs) offer strong spatiotemporal priors for embodied observation--action modeling. However, joint-space action vectors lack ex

researcharxiv-cs-ro

Evaluating Language Model Safety Across Long Adversarial Conversations

arXiv:2609.38357v1 Announce Type: new Abstract: Conversational safety evaluations often test language models with a single harmful prompt, even though real-world systems interact with users through lo

safetyarxiv-cs-cl

Inline Memory Meets Reusable Skills: Memory-centric Framework for Vision-Language-Action Model

arXiv:2609.39794v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have shown strong promise for general-purpose robotic manipulation, yet adapting them to new tasks and domains remai

Applications

L1-MPPI: L1 Adaptive Model Predictive Path Integral for Agile UAV Control

arXiv:2609.38467v1 Announce Type: new Abstract: This work proposes the L1 Adaptive Model Predictive Path Integral (L1-MPPI). It cascades L1 adaptive control with the Model Predictive Path Integral (MP

applicationsarxiv-cs-ro

Looped Diffusion Transformer

arXiv:2609.40305v1 Announce Type: new Abstract: Improving text-to-image models has traditionally relied on increasing model size or the number of denoising steps. In this work, we explore an alternati

Agents

Physis-Lang: Self-Evolving Language as a Physical Representation for Video World Model

arXiv:2609.40358v1 Announce Type: new Abstract: Video world models are expected to predict how the physical world evolves, yet they often produce visually plausible videos that violate basic physical

agentsarxiv-cs-cv

RSI-Master: Structuring Experiments to Guide Autonomous Model Improvement

arXiv:2609.35561v2 Announce Type: replace Abstract: Recursive self-improvement (RSI) seeks to enable AI systems to participate in improving their own capabilities. A concrete pathway is autonomous mod

Safety Monitors Mostly Catch What the Model Already Refuses

arXiv:2609.05797v3 Announce Type: replace Abstract: Safety monitors are evaluated by recall on harmful prompts, regardless of whether the target model would answer them. Yet a monitor matters most on

safetyarxiv-cs-cl

Dagger: Decoupling-based Model Stealing Attack against Graph Neural Networks

arXiv:2609.37972v1 Announce Type: cross Abstract: As Graph Neural Networks (GNNs) are widely deployed as Machine Learning-as-a-Service (MLaaS) APIs, model stealing attacks have emerged as a critical s

Evaluating and Benchmarking the System One Model Jev

arXiv:2609.37647v1 Announce Type: cross Abstract: Jev is a commercial System One model from TypeSafe AI that does not generate text: given a state and typed questions, it returns a choice from fixed o

LongHarness Bench: Stress-Testing Language Model Harnesses for Long-Context Reasoning

model-releasesarxiv-cs-cl

arXiv:2609.38137v1 Announce Type: new Abstract: Language-model (LM) harnesses enable LMs to operate effectively over long contexts using additional compute. However, existing long-context evaluations

Applications

Matrix-game 2.0: An open-source, real-time, and streaming interactive world model

arXiv:2508.13009v5 Announce Type: replace Abstract: Recent advances in interactive video generations have demonstrated diffusion model's potential as world models by capturing complex physical dynamic

applicationsarxiv-cs-cv

Local Ai

Pretrain Once, Route Anywhere: Towards a Foundation Model for LLM Routing

arXiv:2609.37362v1 Announce Type: new Abstract: Large language model (LLM) routing aims to assign each query to the most suitable model from a heterogeneous candidate pool, improving the quality--effi

local-aiarxiv-cs-ai

StateTape: Action-Conditioned Evidence Lifecycle Modeling for Long-Horizon Coding Agents

arXiv:2609.36319v1 Announce Type: new Abstract: Despite the recent success of coding agents built on large language models, it remains challenging to run them over long horizons, since every observati

Think Before You Score: Thinking Reward Model for Visual Generation

arXiv:2609.37372v1 Announce Type: new Abstract: Visual reward models are essential for evaluating and improving visual generation models, yet existing approaches typically map task conditions and cand

safetyarxiv-cs-cv

TomoTransformer: Towards a Foundation Model for CT Reconstruction

arXiv:2609.37605v1 Announce Type: new Abstract: Supervised deep learning has advanced sparse-view tomographic reconstruction. However, conventional models, which typically map filtered back-projection

A Surgical Foundation Model Reveals Task-Dependent Label Efficiency

arXiv:2609.31821v1 Announce Type: new Abstract: Developing label-efficient models is a central challenge in surgical AI due to the high cost and scarcity of expert annotation. While self-supervised fo

GT-PSSM: Unified Probabilistic Framework for Stochastic Dynamics Modeling and Dependency Learning in Multivariate Time Series Anomaly Detection

arXiv:2609.34161v1 Announce Type: cross Abstract: Multivariate time series anomaly detection (MTAD) is crucial for ensuring the safe and reliable operation of complex systems. Many existing methods le

tutorialsarxiv-cs-lg

HM-ROUTER: Joint Model and Harness Routing for Agentic Systems

arXiv:2609.32213v1 Announce Type: new Abstract: Agent performance depends on both the underlying model and the harness that manages its tool use and execution. Selecting a suitable pair requires accou

Neural Proposals, Symbolic Guarantees: Neuro-Symbolic Graph Generative Modeling

arXiv:2602.16954v3 Announce Type: replace Abstract: While deep generative models excel at capturing graph data distributions, they struggle to satisfy complex, hard constraints. In unconstrained setti

Optimizing the Phi-2 Small Language Model for Real-time Chatbot Applications Using Parameter-Efficient Fine-Tuning (PEFT) with QLoRA Quantization

arXiv:2609.33927v1 Announce Type: new Abstract: This study explores the optimization of the Phi-2 Small Language Models (SLMs) for real-time chatbot applications through Parameter-Efficient Fine-Tunin

Steering Language Model Goals with Value Transplant

arXiv:2609.34056v1 Announce Type: new Abstract: Reasoning models often act as if they pursue goals, but their efforts are not always directed toward what users intend, sometimes leading them to pursue

TriDrive: Joint Driver, Vehicle, and Road Modeling for Forecasting and Driver Monitoring

arXiv:2609.33000v1 Announce Type: cross Abstract: Predicting how drivers, vehicles, and road scenes interact and evolve together is central to driver monitoring. Prior work models in-cabin activity or

Aim Short to Reach Far: Your Frozen World Model Can Plan Better Than You Think

arXiv:2609.30036v1 Announce Type: new Abstract: Planners built on visual world models commonly score each predicted outcome by its distance to the encoded goal image. We show that this target can limi

Agents

Dual-Frontier: When Can an Agent Trust Its World Model?

arXiv:2609.26293v2 Announce Type: replace Abstract: Learned world models are becoming essential to general-purpose agents: by predicting action consequences, they support planning and decision-making

agentsarxiv-cs-ai

R-DEIM Net: An Efficient Rationale-Augmented Dual-Expert Interaction Model for Paraphrase Detection

arXiv:2609.30100v1 Announce Type: cross Abstract: Recent advances in paraphrase detection reveal a fundamental trade-off: large language models achieve high accuracy but require high computation, whil

Stream Recursion Model (SRM)

arXiv:2609.28809v1 Announce Type: new Abstract: Mechanistic interpretability seeks to make verifiable statements about the internal behavior of large language models (LLMs). Many interpretability tech

Design and Modeling of a Single-Port Three-Arm Robotic Tool for Minimally Invasive Neurosurgery

arXiv:2609.27099v1 Announce Type: new Abstract: Surgical robots require highly dexterous and compact robotic systems capable of operating effectively within confined anatomical spaces. However, due to

researcharxiv-cs-ro

24 Sept 2026

Latent evolving World Action Model

arXiv:2609.27455v1 Announce Type: new Abstract: World Action Models (WAMs) jointly model action generation and environment dynamics and are mostly built on pretrained Video Diffusion Models (VDMs). In

safetyarxiv-cs-cv

24 Sept 2026

AIBuildAI-2.5: Efficient Autonomous AI Model Development Through LLM-Guided Tree Search

model-releasesarxiv-cs-cl

arXiv:2609.25047v1 Announce Type: new Abstract: Autonomous agents that automatically build artificial intelligence (AI) models could broaden access to AI across science and engineering. A popular line

23 Sept 2026

An Action Is Worth One Patch: Unified World-Action Modeling with PatchWAM

model-releasesarxiv-cs-ro

arXiv:2609.25961v1 Announce Type: new Abstract: Generative visual models offer a foundation for learning representations of physical dynamics, yet their extension to continuous control raises a fundam

23 Sept 2026

Quantifying Protocol-Induced Uncertainty in Comparative Predictive-Model Evaluation: Evidence from Large-Scale Daily PM10 Forecasting

arXiv:2609.26288v1 Announce Type: new Abstract: Comparative studies of predictive models often end by ranking candidate models, yet these rankings depend on evaluation protocols whose influence is rar