Search: “models”

Residual Learning in Empirical Asset Pricing

arXiv:2610.09613v1 Announce Type: cross Abstract: Shallow models are special cases of deep models, and deep models theoretically have the potential to outperform the shallow ones. However, the existin

researcharxiv-cs-lg

8 Oct 2026

Can We Model the Artifacts Explicitly? Disentangle Artifacts via Pairwise Edit Relations for Image Manipulation Localization

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DGX agent

arXiv:2610.07916v1 Announce Type: new Abstract: Image Manipulation Localization (IML) is commonly formulated as a fully supervised learning task that estimates the optimal manipulation mask y for a gi

researcharxiv-cs-cv

7 Oct 2026

DLoop: Looped Speculative Decoding

arXiv:2610.07659v1 Announce Type: new Abstract: Speculative decoding accelerates autoregressive generation in large language models. In each drafting stage, a lightweight draft model proposes tokens t

researcharxiv-cs-cl

Language-model ratings of depression reflect the rater more than the patient

arXiv:2610.08501v1 Announce Type: cross Abstract: Depression has no diagnostic blood test. Language models promise tireless, consistent assessment, but can accurate raters disagree about individuals?

Learning in Dreams, Winning in Reality: A Continuous Dyna Loop for a Ten-Hero MOBA

arXiv:2610.08033v1 Announce Type: new Abstract: World models are usually judged from the inside: by prediction loss, by the return a policy earns in imagination, or by how convincing their frames look

Learning to Remember: Distilling Memory Retention for Compact Recurrent Neural Networks

model-releasesarxiv-cs-lg

arXiv:2610.06942v1 Announce Type: new Abstract: Deep learning models, particularly recurrent neural networks and their variants, such as long short-term memory, have significantly advanced time series

AdaptInfer: Adaptive Token Pruning for Vision-Language Model Inference via Dynamical Text Guidance

arXiv:2508.06084v3 Announce Type: replace Abstract: Vision-language models (VLMs) have achieved impressive performance on multimodal inference tasks, but the cost remains a significant challenge due t

researcharxiv-cs-cv

Closing the Context Gap: Activation Alignment for Tabular In-Context Learning

model-releasesarxiv-cs-lg

arXiv:2610.06679v1 Announce Type: new Abstract: Tabular foundation models perform in-context learning (ICL) by conditioning predictions on labeled training examples provided as context. Unlike traditi

Agents

DreamTest: World-Model Surrogates for Search-Based Testing of Deep Reinforcement Learning Agents

arXiv:2610.04494v1 Announce Type: cross Abstract: Testing deep reinforcement learning (DRL) agents in cyber-physical systems aims to uncover diverse failures before deployment, but each execution can

agentsarxiv-cs-lg

ForeAct3D: Policy-Grounded Future World Modeling for VLA Policies

arXiv:2610.04607v1 Announce Type: cross Abstract: Robots need to anticipate how their actions will change the world, since manipulation success hinges on the resulting contacts and object motions. How

safetyarxiv-cs-cv

MambaVF: State Space Model for Efficient Video Fusion

arXiv:2602.06017v2 Announce Type: replace Abstract: Video fusion aims to integrate complementary information from multiple source videos while preserving temporal consistency. Effective modeling of te

safetyarxiv-cs-cv

THYME: Temporal Hierarchical-Cyclic Interactivity Modeling for Video Scene Graphs in Aerial Footage

arXiv:2507.09200v2 Announce Type: replace Abstract: The rapid proliferation of video in applications such as autonomous driving, surveillance, and sports analytics necessitates robust methods for dyna

When Are Concept Bottleneck Model Explanations Faithful and Compact?

arXiv:2610.06285v1 Announce Type: new Abstract: Concept bottleneck models (CBMs) are neural classifiers that allow to explain their decisions via high-level concepts, potentially enabling understandin

researcharxiv-cs-lg

Benchmarking Literature Retrieval for a Model Organism: A Dictyostelium Case Study

arXiv:2610.03130v1 Announce Type: cross Abstract: Biological literature retrieval systems are often developed and evaluated using broad biomedical corpora and general-purpose search tasks. However, ma

Collective Bias Mitigation via Model Routing and Collaboration

arXiv:2610.03240v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed in public health, finance, and governance, requiring both accuracy and societal value alignment.

safetyarxiv-cs-cl

Efficient Reasoning Training Does Not Always Harm CoT Faithfulness and Monitorability

arXiv:2610.03509v1 Announce Type: new Abstract: Chain-of-thought (CoT) reasoning allows humans to inspect how large language models reach their answers, and oversee model behaviour. This reasoning com

Harness-Aware Distillation for Small Language Model Agents

arXiv:2610.02858v1 Announce Type: new Abstract: Language model agents are deployed with a harness, the software around the model that manages its context, tools, and feedback. When such an agent is di

Investigating the Role of Reasoning-Language Alignment in Monolingual Retrieval-Augmented Generation

arXiv:2610.03136v1 Announce Type: new Abstract: Reasoning traces improve large language models (LLMs), but current models are trained to reason mostly in English. It has been shown that forcing a mode

LiteEMG-FM: An Efficient and Deployable Foundation Model for Robust EMG Sensing

arXiv:2610.02497v1 Announce Type: new Abstract: Electromyography (EMG) signals vary substantially across individuals, body regions, recording sessions, and sensing hardware, limiting the generalizatio

local-aiarxiv-cs-lg

Parasitic Co-Denoising: Unlocking 3D Human Motion Generation in a Frozen Video Diffusion Model

arXiv:2610.03047v1 Announce Type: new Abstract: Despite never being supervised on explicit 3D motion, large-scale text-to-video diffusion models synthesize realistic human motion in their generated vi

safetyarxiv-cs-cv

ViTok: Improving Dense Semantics in AM-RADIO-Style Multi-Teacher Distillation with PHI-S and Masked Image Modelling

arXiv:2610.02903v1 Announce Type: new Abstract: We study how to consolidate the current VITOK progress into a single multi-teacher distillation recipe that jointly preserves global recognition and den

A Structured State Space Sequence Model for Multi-Class Classification of Malware

arXiv:2610.01893v1 Announce Type: cross Abstract: By 2030, Internet of Things (IoT) devices are projected to reach 40 billion, with fast-paced technological advancements in fields such as industry, he

applicationsarxiv-cs-ai

Ego2Act: Evaluating Goal-Directed Manipulation in Egocentric Video Generation

arXiv:2610.01092v1 Announce Type: new Abstract: Video generation models are increasingly being explored as world simulators for embodied planning and learning. To do so effectively, these models must

False Floors: LLM Safety Routing Evaluations Break Under Distribution Shift

model-releasesarxiv-cs-ai

arXiv:2610.01535v1 Announce Type: cross Abstract: Safety routers send each request to one of several models and are judged against the best single model. A major routing benchmark picks that comparato

FedMIX-P: Mixing Local and Global Preconditioners for Federated Vision and Language Model Training

arXiv:2610.01515v1 Announce Type: cross Abstract: Adaptive preconditioners accelerate model training, but heterogeneous client geometries can bias federated updates even when gradients are evaluated a

local-aiarxiv-cs-ai

GIFTBench: Diagnosing Generalization in Image Forgery Localization and Informing Model Design

arXiv:2610.01778v1 Announce Type: new Abstract: Reliable evaluation of image forgery localization (IFL) requires assessing models under diverse distribution changes, yet existing benchmarks often cove

Manifold-Constrained Initial Noise Optimization for Efficient Generative Model Alignment

arXiv:2610.00365v1 Announce Type: cross Abstract: Recent advances in distillation and flow-map models have enabled deterministic one- or few-step generation for high-quality data, facilitating a new b

SkeleWAM: Skeleton World-Action Modeling for Efficient Robotic Manipulation

model-releasesarxiv-cs-ro

arXiv:2610.02120v1 Announce Type: new Abstract: World action models (WAMs) combine robot action generation with future state prediction. Existing WAMs typically predict videos or learned visual latent

STCFormer: Adaptive Spatio-Temporal Modeling with Dynamic Cluster Transformer for Station-based Weather Forecasting

arXiv:2610.00377v1 Announce Type: new Abstract: Station-based weather forecasting supports daily life and economic activity, yet accurate forecasts require modeling complex spatial dependencies among

applicationsarxiv-cs-lg

Structured-Noise Masked Modeling for Video, Audio and Beyond

arXiv:2503.16311v2 Announce Type: replace-cross Abstract: Masked modeling has emerged as a robust self-supervised learning framework. However, most methods rely on random masking, which disregards the

Argument Structure Prediction in Online Conversations: A Comparative Study of Modeling Paradigms and Task Architectures

arXiv:2609.39225v1 Announce Type: new Abstract: Argument structure prediction (ASP) constructs complete argument structures from discourse by identifying argumentative units and their relations. While

BayesNDE: Bayesian Generative Modeling for Neural Density Estimation

arXiv:2609.39843v1 Announce Type: cross Abstract: Density estimation is a fundamental problem in statistics and machine learning. In this work, we introduce BayesNDE, a neural density estimator based

applicationsarxiv-cs-ai

Decode-Latency Feedback Prefill: A Model-Free Controller and Its Generalization Limits

arXiv:2609.38386v1 Announce Type: new Abstract: Concurrent autoregressive inference creates a fundamental interference problem: prefilling a newly arrived long prompt can delay tokens for requests tha

local-aiarxiv-cs-ai

Demographic Pluralism: Inference-Time Modeling of Pluralistic Human Preference Distributions

arXiv:2609.38555v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used in culturally sensitive settings, where alignment requires representing diverse preferences within po

Agents

Does This Action Still Explain the Task? Reverse Scoring for Diffusion Language Model Agents

arXiv:2609.38536v1 Announce Type: cross Abstract: Diffusion-based large language models (dLLMs) promise to break the sequential latency bottleneck of autoregressive agents through parallel decoding, b

agentsarxiv-cs-ai

Evaluating Persistent Calibration under Evolving Model Knowledge

arXiv:2609.38797v1 Announce Type: cross Abstract: As AI systems move from static repositories to agents that are capable of continual adaptation and learning, maintaining their trustworthiness means e

Forging LLM Authorship Fingerprints with Targeted Rewriting

arXiv:2609.38831v1 Announce Type: new Abstract: Model-attribution classifiers can often identify which language model produced a text, making model-specific writing patterns a signal of provenance. Ac

researcharxiv-cs-cl

H-WM: Robotic Task and Motion Planning Guided by Hierarchical World Model

arXiv:2602.11291v3 Announce Type: replace Abstract: World models are becoming central to robotic planning and control by predicting future state transitions. Existing approaches mainly rely on visual,

researcharxiv-cs-ro

RESUME: Recurrent State Updates from Motion and Residual Signals for Efficient Video Language Modeling

arXiv:2609.39563v1 Announce Type: new Abstract: Existing video language models encode sampled RGB frames independently, so a long video must either exhaust the token budget or drop the changes between

researcharxiv-cs-cv

TopTimeNet: Topologically-assisted time-series classification model

model-releasesarxiv-cs-lg

arXiv:2609.39792v1 Announce Type: new Abstract: Distinguishing periodic from chaotic dynamics in a time series is a fundamental challenge in both physics and engineering. Yet, end-to-end learned archi

Working Around the Compute Ceiling: Byte-Exact Memory in Galahad Makes LLM Reading a One-Time Cost LLM Reading a One-Time Cost

model-releasesarxiv-cs-ai

arXiv:2609.39358v1 Announce Type: cross Abstract: A transformer language model performs a bounded amount of computation per token, and recent work by Vishal Sikka, former CEO of Infosys, argues that t

CRASM-Gate: Deterministic-First Constraint- and Role-Aware Semantic Mapping with Selective Model Assistance Across Heterogeneous Industrial Standards

arXiv:2609.37458v1 Announce Type: new Abstract: Industrial standards often encode the same engineering concept through incompatible hierarchies, identifiers, roles, and structural constraints, so the

local-aiarxiv-cs-ai

Cross-Organizational SysML Model Integration: A Survey of Challenges and AI-Supported Tasks

arXiv:2609.37000v1 Announce Type: cross Abstract: Cross-organizational collaboration is widely regarded as a key promise of SysML-based Model-Based Systems Engineering (MBSE), yet practitioners still

Larry Caused the Car to Stop, But the Model Didn't Notice: Transformer Blindness to the M-Heuristic

arXiv:2609.37497v1 Announce Type: new Abstract: Modern transformer models excel at capturing semantic relationships through sentence embeddings, yet their ability to perform pragmatic reasoning remain

Learning Beyond What You Sample: Off-Policy-Aware Cross-Model Trajectory Exchange for RLVR

arXiv:2609.37868v1 Announce Type: cross Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) methods such as GRPO rely on successful self-generated trajectories, but finite rollout budgets

MeteoVerse: Unified Weather-Controllable Video World Model

arXiv:2609.36810v1 Announce Type: new Abstract: Video world models aim to predict future content from an observed scene while following prescribed camera motion. Real-world scene evolution is determin

applicationsarxiv-cs-cv

Transolver-sigma: Joint Spectral-Physical Subspace Modeling for Neural PDE Solving

model-releasesarxiv-cs-ai

arXiv:2609.37279v1 Announce Type: new Abstract: Neural solvers offer efficient surrogates for numerical simulation of partial differential equations (PDEs). For time-dependent problems, strong one-ste

Visual Anomaly Synthesis for Model Selection in Data Scarcity

arXiv:2609.37360v1 Announce Type: new Abstract: Defect detection systems for industrial condition monitoring can only be relied upon if they are validated, yet defective samples are rare and, for a sp

applicationsarxiv-cs-cv