Search: “models”

MIAR: Medical Image Super-Resolution With Autoregressive Modeling

arXiv:2609.26103v1 Announce Type: new Abstract: Medical Image Super-Resolution (MISR) aims to enhance spatial resolution without requiring hardware modifications. Although deep learning has yielded pr

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Qwen3.8-Omni: Towards Native Omni-Modal Agents

DGX agent

arXiv:2609.25611v1 Announce Type: new Abstract: We introduce Qwen3.8-Omni-Flash, a natively multimodal agentic model for real-world multimodal productivity. Compared with previous omni models, which p

model-releasesarxiv-cs-cl

23 Sept 2026

Rewired or Gated? How Instruction Tuning Shapes Knowledge-Conflict Circuits in LLMs

arXiv:2609.25602v1 Announce Type: cross Abstract: In language models, the choice between believing the prompt and believing the weights is made by a handful of identifiable attention heads. Instructio

Safety-Constrained Model Predictive Control for an Omnidirectional Walking Assistive Robot Using Control Barrier Function

arXiv:2609.25994v1 Announce Type: new Abstract: Providing safe and effective mobility assistance plays a crucial role in restoring independence and enhancing the quality of life for individuals with m

safetyarxiv-cs-ro

SEABED: SouthEast Asian Benchmark for Evaluating Audio Reasoning

arXiv:2609.22586v1 Announce Type: cross Abstract: Modern audio-language models are no longer judged only on what words they can transcribe, but on whether they can reason over what they hear: recoveri

SelfOp: An Optimization Algorithm for Self-Improving Security Agents

arXiv:2609.22792v1 Announce Type: cross Abstract: LLM agents are increasingly used for security tasks: vulnerability discovery, exploit reproduction, and patch generation. Improving them at the model

SSP-Bench: A Hybrid Data Generation Framework for Safety, Security, and Privacy Evaluation

arXiv:2609.25352v1 Announce Type: cross Abstract: Evaluation of large language models (LLMs) for safety, security, and privacy (SSP) relies heavily on static benchmarks, which suffer from score satura

TimeLitmus: A Diagnostic Benchmark for Cross-Modal Understanding and Explanation Faithfulness in Event-Conditioned Time-Series Prediction

arXiv:2609.24677v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used to make predictions from numerical time-series histories and textual events. Yet accuracy alone canno

When Agentic Trust Crosses Organizational Boundaries: Structural Externalization and a Reference Model for Trust Evidence

arXiv:2609.22961v1 Announce Type: cross Abstract: Agentic systems increasingly invoke tools, services, data, and other agents across organizational boundaries, yet a relying party cannot assess a dele

safetyarxiv-cs-ai

Accurate Motion Estimation with Bezier Control Point for Efficient Frame Interpolation

arXiv:2609.23408v1 Announce Type: new Abstract: In frame interpolation tasks, motion ambiguity in the training set causes models to generate blurry intermediate frames. Moreover, the assumption of uni

Tutorials

AffordanceWAM: Affordance-Aware Joint World-Action Modeling for Robot Manipulation

arXiv:2609.22332v1 Announce Type: cross Abstract: Generalizable robot manipulation requires predicting how a scene will evolve, identifying where interactions are feasible, and determining how to act.

tutorialsarxiv-cs-cv

Complex KDA: Understanding and Enhancing the Expressivity of Kimi Delta Attention

arXiv:2609.24797v1 Announce Type: new Abstract: Linear RNNs based on the delta-rule enable efficient sequence modeling, but their linear updates with a low-rank correction constrain their expressivity

Applications

CompVLA: A Variable Compliance Vision-Language-Action Model for Contact-rich Manipulation

arXiv:2609.23614v1 Announce Type: new Abstract: Contact-rich manipulation, requiring robots to regulate not only motion but also how they yield to external forces, has emerged as the next frontier for

applicationsarxiv-cs-ro

CrowdCue: Specialist-Cue Conditioning for Vision-Language Crowd Counting

arXiv:2609.23012v1 Announce Type: new Abstract: Generative vision-language models (VLMs) offer a counting paradigm in which one model produces both a count and a natural-language account of the scene,

Efficient Mixture-of-Experts with Speculative Decoding via Expert Coactivation

arXiv:2609.22471v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) models are increasingly deployed alongside Speculative Decoding (SD) to accelerate inference, but combining the two is challe

GenVoid: Uncertainty-Aware Learning of Subsurface Material Defects with an Experimentally Validated Physics-Informed Generative Model

arXiv:2609.23761v1 Announce Type: new Abstract: Internal voids are ubiquitous defects in manufactured structures, yet their characterization remains challenging because their geometry is hidden and ca

researcharxiv-cs-lg

Hi-Singers: A Comprehensive High-Quality Dataset for Expressive Audio-Driven Singing Head Synthesis

arXiv:2609.22264v1 Announce Type: cross Abstract: State-of-the-art models for audio-driven digital human generation have achieved photo-realistic results in talking-head synthesis. However, extending

Imagine-RL: Residual-Confidence-Guided Cross-Attention for World-Model-Augmented VLA Reinforcement Learning

arXiv:2609.24033v1 Announce Type: new Abstract: Reliable action evaluation in contact-rich manipulation requires looking beyond the current observation to future visual and contact consequences. Exist

safetyarxiv-cs-ro

List Counting Failures Are Not One Phenomenon

arXiv:2609.22230v1 Announce Type: new Abstract: Counting the items in a bracketed list looks trivial, yet open-weight chat models often get it wrong. Prior work usually blames input bottlenecks such a

Measuring the Assistant's Harmlessness Preferences on the User Turn

arXiv:2609.23935v1 Announce Type: new Abstract: Post-training turns a general next-token predictor into a chat model with a persistent assistant persona. If that persona is a character the model plays

local-aiarxiv-cs-cl

Agents

Prediction of Nonlinear Oscillations in a Jumping Quarter-Car Model Using Reservoir Computing

arXiv:2609.22205v1 Announce Type: new Abstract: Reliable prediction of vehicle dynamics is essential for smart driving applications such as autonomous control and advanced driver-assistance systems. O

agentsarxiv-cs-lg

Probabilistic Modelling of Operational Design Domains, A New Approach for Testing AI Systems

arXiv:2609.24397v1 Announce Type: new Abstract: The conventional testing process quickly fails when applied to ML-based systems such as obstacle detection in vehicles: if an obstacle is not detected i

researcharxiv-cs-lg

RL-STaR: Theoretical Analysis of Reinforcement Learning Frameworks for Self-Taught Reasoner

arXiv:2410.23912v3 Announce Type: replace-cross Abstract: The reasoning abilities of large language models (LLMs) have improved with chain-of-thought (CoT) prompting, allowing models to solve complex

SCALE: Simulation-Calibrated Amortized Learning for Energy Materials (A hybrid architecture connecting deterministic modeling, real-world data, and transformer-scale inference for accelerated energy-materials discovery)

arXiv:2609.22233v1 Announce Type: new Abstract: Energy systems face converging pressures for security, affordability, resilience, and sustainability, creating a need for faster discovery of deployable

local-aiarxiv-cs-lg

Time-Incremental Continued Pretraining of LLMs: Knowledge Updates Without Catastrophic Forgetting

arXiv:2609.23916v1 Announce Type: new Abstract: Large language models (LLMs) drift out of date the moment their pretraining ends, yet retraining from scratch is prohibitively expensive. Continued pret

Tool-Augmented On-Policy Distillation for LLM Domain Adaptation in Sequence-Based Omics Tasks

arXiv:2609.23435v1 Announce Type: cross Abstract: Multi-omics sequences contain complex biological patterns, yet deciphering their mechanisms for automated scientific discovery remains challenging. As

TRACE: Tractable Routing Autoencoder for Clinical ECG

arXiv:2609.23460v1 Announce Type: new Abstract: Deep learning has advanced automated electrocardiogram (ECG) diagnosis, but the field's most accurate models, foundation models pretrained on millions o

What Is The Political Content in LLMs' Pre- and Post-Training Data?

arXiv:2509.22367v3 Announce Type: replace Abstract: Large language models (LLMs) reflect politically-slanted opinions in their generated text. Even though it is widely assumed that model behavior stem

researcharxiv-cs-cl

When Does Learning Beat Heuristics? A Case Study in Kubernetes Scheduler Score Plugins

arXiv:2609.22142v1 Announce Type: cross Abstract: Kubernetes scheduler plugins that score candidate nodes are, in production, hand-tuned heuristics. We ask whether a learned scoring function - trained

Which Part of the Context Layer Does the Work? Separating Semantic Content from Retrieval Scaffolding in Text-to-SQL Agents

arXiv:2609.22259v1 Announce Type: new Abstract: Context layers, curated documentation that an analytics agent fetches at query time, produce large accuracy gains on text-to-SQL benchmarks. A with/with

Beyond Atomic Tokens: Factorizing Syllables for Language Model Pretraining

arXiv:2609.21362v1 Announce Type: new Abstract: Conventional tokenizers represent text as characters or statistically derived subwords, overlooking the internal phonological structure of syllables and

researcharxiv-cs-cl

Dynamic Modeling and LQR Control of a Single Coaxial Drone with 2DOF Thrust Vectoring Mechanism

arXiv:2609.21099v1 Announce Type: new Abstract: Coaxial rotor drones have generated considerable interest because of energy efficiency and small size, but they are afflicted with inherent underactuati

researcharxiv-cs-ro

Edit-VAR: Taming Visual Autoregressive Model for Precise Video Editing

arXiv:2609.21268v1 Announce Type: new Abstract: Text-guided video editing modifies target content while preserving the appearance and temporal coherence of unedited regions. Training-based approaches

researcharxiv-cs-cv

EnterpriseVal: Quantifying the Efficacy, Reliability and Value of Generative AI in the Enterprise

arXiv:2609.21841v1 Announce Type: new Abstract: Frontier language models now produce professional deliverables that expert graders judge to match human work on a substantial share of economically valu

Hand-Aware Transition Modeling for Bimanual Procedural Anomaly Detection

arXiv:2609.21207v1 Announce Type: new Abstract: Procedural anomaly detection in bimanual assembly requires judging each hand action against the execution so far. A corrective action may look unusual i

researcharxiv-cs-cv

OmniVChat: Synthesizing, Benchmarking, and Training for Native Audio-Visual Dialogue

arXiv:2609.21465v1 Announce Type: cross Abstract: We define OmniVChat (Omni Video Chat) as the task of native audio-visual dialogue between a user and an omni model. In OmniVChat, omni models directly

SignGPT: Toward LLM-Mediated Sign Language Interaction through Gloss-Free Translation and Generation

arXiv:2609.21709v1 Announce Type: new Abstract: Large language models (LLMs) provide limited support for sign language interaction. Unifying sign language translation (SLT) and generation (SLG) to ena

Tutorials

Skel-WAM: A Hand-Skeleton-Conditioned World Action Model for Human-to-Robot Manipulation Transfer

arXiv:2609.21514v1 Announce Type: new Abstract: Robot demonstrations are expensive to collect and often provide limited distributional coverage of task variations. Human videos offer a low-cost source

tutorialsarxiv-cs-ro

SP-MoMamba: Superpixel-driven Mixture of State Space Experts for Efficient Image Super-Resolution

arXiv:2605.25892v2 Announce Type: replace Abstract: State space models (SSMs) have emerged as an efficient paradigm for single-image super-resolution (SR) due to their linear complexity and long-range

local-aiarxiv-cs-cv

Triply-Scalable Equivariant Gaussian Process Modeling

arXiv:2609.21085v1 Announce Type: cross Abstract: Gaussian processes (GPs) provide principled probabilistic predictions while encoding prior knowledge, including equivariances. Yet, their use in large

researcharxiv-cs-lg

VidOmni-Bench: A Benchmark for Fine-Grained Video Understanding via Spatio-Temporal Event Verification across Complexity and Duration

arXiv:2609.21521v1 Announce Type: cross Abstract: While Video Large Language Models (Video-LLMs) have recently demonstrated strong performance, reliably evaluating their fine-grained video understandi

When AI Reviews Train AI Reviewers: Scientific-Judgment Collapse and Mitigation

arXiv:2609.20942v1 Announce Type: new Abstract: Large language models (LLMs) increasingly participate in scientific evaluation, both as automated reviewers and as assistants to human reviewers. As mod

Accelerating Visual Policy Learning with Sampling-Based Model Predictive Control

arXiv:2609.20575v1 Announce Type: cross Abstract: Learning visual policies for locomotion and manipulation requires coordinating contact with the environment and can incur substantial computation and

local-aiarxiv-cs-ai

An Architecture for Long-Horizon Agents: Levels, Ticks and Cascaded Intelligence

arXiv:2609.19519v1 Announce Type: new Abstract: Language-model agents are increasingly asked to carry out work spanning days or weeks, such as an operations remediation or a research programme. Such a

DeepSeek-V4.1-Flash: Pushing the Limits of KV Cache Compression

arXiv:2609.19969v1 Announce Type: new Abstract: The widespread adoption of long-horizon agents has made model workloads increasingly input-heavy. Although prior work has substantially reduced the cost

Geometrically-Constrained Radar-Inertial Odometry via Continuous Point-Pose Uncertainty Modeling

arXiv:2604.02745v2 Announce Type: replace Abstract: Radar odometry is crucial for robust localization in challenging environments; however, the sparsity of reliable returns and distinctive noise chara

local-aiarxiv-cs-ro

Labeled Incidence Structures for Native Transformer Modeling of Text, Knowledge Graphs, and Hypergraphs

arXiv:2609.20278v1 Announce Type: cross Abstract: Text, knowledge graphs, and hypergraphs all have elements that play distinct roles within relation instances, structure that is lost when data is flat

safetyarxiv-cs-ai

Agents

Language-model groups overstate consensus when replaying human deliberation on a reasoning task

arXiv:2609.20543v1 Announce Type: new Abstract: Full-consensus rates are often treated as indicators of collective cognition, yet depend on how participation and final states are operationalized. We r

agentsarxiv-cs-ai