Search: “models”

arXiv:2608.07074v1 Announce Type: new Abstract: Dense point cloud maps, as a typically used mapping representation, are difficult to deploy on resource-constrained robots because their memory consumpt

local-aiarxiv-cs-ro

10 Aug 2026

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Local Ai

MiCoPro: End-to-End Mixed Precision HW/SW Co-design with HW-aware Proxy Model

DGX agent

arXiv:2608.06916v1 Announce Type: new Abstract: Quantized Neural Networks~(QNN) with low-bitwidth data have proven promising in efficient storage and computation on edge devices. To mitigate accuracy

local-aiarxiv-cs-lg

10 Aug 2026

PAST: Prompt-Adaptive Sampling Termination for Efficient Diffusion Model

arXiv:2608.06794v1 Announce Type: new Abstract: While diffusion models have made significant progress in text-to-image tasks, they still exhibit limitations when directly optimizing downstream objecti

safetyarxiv-cs-cv

10 Aug 2026

AppDeltaWorld: Transition-Grounded Delta Code World Model for Mobile GUI Agents

arXiv:2608.05891v1 Announce Type: new Abstract: Mobile GUI agents can operate apps through pixel perception and touch actions, making them a promising interface for collecting and improving long-horiz

safetyarxiv-cs-ai

Tutorials

Cautious Context Steering for Language Model Personalization

arXiv:2608.05813v1 Announce Type: new Abstract: Personalizing language models (LMs) to individual user preferences is essential for aligning responses with diverse goals and backgrounds. Existing meth

tutorialsarxiv-cs-ai

Disentangling 3D Modeling from Spatial Reasoning

arXiv:2608.05242v1 Announce Type: cross Abstract: In this work, we explore an alternative paradigm for spatial reasoning by explicitly disentangling 3D perception from reasoning, rather than jointly a

agentsarxiv-cs-cv

Applications

MMaDA-VLA: Large Diffusion Vision-Language-Action Model with Unified Multi-Modal Instruction and Generation

arXiv:2603.25406v3 Announce Type: replace Abstract: Vision-Language-Action (VLA) models map visual observations and natural-language instructions to robot actions; however, hierarchical and autoregres

applicationsarxiv-cs-ro

Applications

omega-0: A Latent Predictive World Action Model for Concurrent Humanoid Loco-Manipulation

arXiv:2608.06375v1 Announce Type: new Abstract: Humanoid household tasks often require concurrent loco-manipulation, where the robot must move, adjust posture, maintain balance, and manipulate objects

applicationsarxiv-cs-ro

Poli-Bias: Understanding and Measuring Large Language Model Biases in International Political Conflicts

arXiv:2608.06123v1 Announce Type: new Abstract: Measuring political bias in large language models (LLMs) remains challenging as it can manifest through subtle differences in framing, argumentation, an

safetyarxiv-cs-ai

Position: It's Time to Optimize LLMs for Self-Consistency

model-releasesarxiv-cs-ai

arXiv:2608.05188v1 Announce Type: cross Abstract: Despite ever-increasing sophistication in language model (LM) pre- and post-training pipelines, many important failures persist: models overcondition

Relay, Don't Route: Adaptive Population Handoff for Cost-Efficient LLM-Driven Evolution

arXiv:2608.05651v1 Announce Type: cross Abstract: Large language model (LLM)-driven evolution has shown promise for program search and algorithm discovery, but relying on strong models throughout long

researcharxiv-cs-ai

Applications

Revisiting Black-Box Model Ownership Verification through Information Theory

arXiv:2409.06130v2 Announce Type: replace-cross Abstract: Modern machine learning models require substantial computational resources and data to train, making them valuable intellectual property. Mode

applicationsarxiv-cs-ai

A geometry-based deep equilibrium model for image restoration under multiplicative Gamma noise

arXiv:2608.04944v1 Announce Type: cross Abstract: We propose a deep learning framework for image restoration from images degraded by both multiplicative Gamma noise and blur. Unlike conventional deep

A Model Merging Approach for Continual MLLM Unlearning

arXiv:2608.04548v1 Announce Type: cross Abstract: Multimodal large language model (MLLM) unlearning methods have been proposed to remove private, sensitive, or proprietary information from well-traine

researcharxiv-cs-ai

AutoProteinEngine: A Large Language Model Driven Agent Framework for Multimodal AutoML in Protein Engineering

arXiv:2411.04440v1 Announce Type: cross Abstract: Protein engineering is important for biomedical applications, but conventional approaches are often inefficient and resource-intensive. While deep lea

agentsarxiv-cs-ai

Canonical Joint Energy-Based Model on CIFAR-10: failure modes and practical indistinguishability of Predictor-Corrector and SGLD samplers

arXiv:2608.05025v1 Announce Type: new Abstract: Joint Energy-Based Models (JEM) unify classification and generation within a single network and support out-of-distribution (OOD) detection. Canonical J

DataRx: Missingness-Aware Sampling for Safer Large Language Model Task-Specific Fine-Tuning

arXiv:2608.04322v1 Announce Type: new Abstract: Task-specific fine-tuning can improve the performance of large language models (LLMs) on downstream tasks. However, our study reveals that task-specific

safetyarxiv-cs-cl

Exact Model-Free Policy Iteration for Co-safe LTL Planning

arXiv:2608.05047v1 Announce Type: cross Abstract: This work studies model-free reinforcement learning for co-safe linear temporal logic (sc-LTL) objectives in finite Markov decision processes, which c

safetyarxiv-cs-ro

Manipulation-Proof Oblivious Audits against Deceptive Model Providers

arXiv:2608.04365v1 Announce Type: new Abstract: Audits have emerged as a critical instrument for algorithmic governance, providing a mechanism for external scrutiny and governance of machine learning

safetyarxiv-cs-lg

MOAT: Model-Agnostic Randomized Transformations for preventing Efficiency Degradation Attacks on ViTs

arXiv:2608.04680v1 Announce Type: cross Abstract: To adopt the Vision Transformers (ViTs) in resource-constrained environment, token pruning is widely used to reduce computational cost without impacti

researcharxiv-cs-cv

OctoLong: Mid-Training On Cross-Repository Code Contexts Enhances Long-Context Modeling

arXiv:2608.05141v1 Announce Type: new Abstract: Context lengths of language models (LMs) have dramatically increased, driven by the demands for in-context learning, self-improvement, and long-horizon

agentsarxiv-cs-ai

Representing Visual Evidence for Item Difficulty Prediction: Visual Textualization and Image-Native Modeling

arXiv:2608.04554v1 Announce Type: new Abstract: Predicting item difficulty from content can provide an initial estimate for newly developed questions before sufficient student responses are available.

The Personalization Mirage: How LLMs Fabricate User Profiles, and Why Self-Monitoring Misleads

arXiv:2608.04570v1 Announce Type: new Abstract: Personalized LLMs with persistent memory are increasingly deployed, yet the faithfulness of their user models remains unexamined. We study over-inferenc

ARCHead: Activation-Metric Residual Correction for Large Language Model Output Heads

arXiv:2608.02703v1 Announce Type: new Abstract: Weight-only quantization substantially reduces the storage of large language model (LLM) transformer blocks, but practical backends often retain the fin

Automatic Patient-Specific Microwave Ablation Planning Accelerated by a Physics-Guided Deep Learning Model

arXiv:2608.03086v1 Announce Type: cross Abstract: Microwave ablation (MWA) is a promising minimally invasive treatment for liver tumors, but its therapeutic outcome strongly depends on patient-specifi

Tutorials

Divide-and-Conquer: Towards Generalizable Amortized Bayesian Inference for the Drift Diffusion Model

arXiv:2608.03566v1 Announce Type: cross Abstract: The drift diffusion model (DDM) is a cornerstone of cognitive decision-making research. Although numerous estimation methods exist, researchers contin

tutorialsarxiv-cs-lg

Hunyuan3D-Buffalo 1.0: A Unified Multimodal Model for Scalable 3D Generation, Understanding, and Editing

arXiv:2608.02711v1 Announce Type: new Abstract: Recent advances in image generation have demonstrated the potential of unified multimodal models that integrate understanding, generation, and editing.

researcharxiv-cs-cv

Modeling Matches as Language: A Generative Transformer Approach for Counterfactual Player Valuation in Football

arXiv:2603.15212v2 Announce Type: replace Abstract: Evaluating football player transfers is challenging because player actions depend strongly on tactical systems, teammates, and match context. Despit

researcharxiv-cs-ai

Quantization Effects on Biomedical LLM Reliability

model-releasesarxiv-cs-lg

arXiv:2608.03854v1 Announce Type: new Abstract: When decoder language models are used as classifiers, predicted class probabilities depend on implementation choices, including the prompt template, ver

Sedentary Behavior Classification for Wearable Sensors with a CNN-BiLSTM Model

arXiv:2608.02946v1 Announce Type: new Abstract: Accurate detection of sedentary behavior is important for studying health risks related to prolonged sitting, but posture-based classification remains c

Simulation-free and finite-time diffusion model

arXiv:2608.03117v1 Announce Type: new Abstract: The performance of generative diffusion models is determined by the choice of the reference diffusion process connecting the empirical and prior distrib

Computational Approaches to Understanding Large Language Model Impact on Writing and Information Ecosystems

arXiv:2506.17467v2 Announce Type: replace Abstract: Large language models (LLMs) have shown significant potential to change how we write, communicate, and create, leading to rapid adoption across soci

EHR2Path: Comprehensive Pathway-Level Modeling of Longitudinal Patient Trajectories from Multimodal Electronic Health Records

arXiv:2506.04831v3 Announce Type: replace-cross Abstract: Forecasting how a patient's condition is likely to evolve, including possible deterioration, recovery, treatment needs, and care transitions,

EndoWAM: A Grounded World-Action Model for Generalizable Endoscopic Navigation

arXiv:2608.01221v1 Announce Type: new Abstract: Autonomous endoscopic navigation can reduce clinicians' operational burden, yet robust control remains challenging due to tissue deformation, transient

safetyarxiv-cs-ro

Enhancing Visual Perception in Foggy Conditions via Multiclass Fog Density Modeling

arXiv:2608.01572v1 Announce Type: new Abstract: Autonomous driving (AD) systems have advanced rapidly over the past decade; however, robust perception under adverse weather conditions remains a major

agentsarxiv-cs-cv

Local Ai

FlowPilot: Real-Time World-Action Modeling for Agile UAV Navigation

arXiv:2608.00635v1 Announce Type: new Abstract: We present FlowPilot, a compact world-action model for real-time onboard UAV navigation from depth. Unlike map-then-optimize pipelines that require loca

local-aiarxiv-cs-ro

Hierarchical Pre-Training of Vision Encoders with Large Language Model

arXiv:2604.00086v2 Announce Type: replace-cross Abstract: The field of computer vision has experienced significant advancements through scalable vision encoders and multimodal pre-training frameworks.

safetyarxiv-cs-cl

Loanword or Switch? The Annotation Boundary, Not the Model, Drives Kazakh-Russian Code-Switching Identification

arXiv:2608.00581v1 Announce Type: new Abstract: Off-the-shelf LID and letter heuristics over-label Kazakh-Russian social text as mixed: Russian loanwords inside Kazakh look like code-switching under a

Local Ai

Local Shapley: Model-Induced Locality and Optimal Reuse in Data Valuation

arXiv:2603.03672v2 Announce Type: replace Abstract: The Shapley value provides a principled foundation for data valuation, but exact computation is #P-hard due to the exponential coalition space. Exis

local-aiarxiv-cs-lg

MedPRESS: A Multi-turn Benchmark for Patient-Pressure-Induced Medical Sycophancy in LLMs

model-releasesarxiv-cs-cl

arXiv:2608.02520v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used for health-related advice. Existing research measures their safety with static questions rather than

MIEScore: Human-Aligned Evaluation for Multi-Source Image Editing

arXiv:2608.02059v1 Announce Type: new Abstract: Recent advances in unified multimodal models have significantly improved text-guided image editing abilities. In particular, models such as Nano-Banana-

Tutorials

Modeling Unknown Nonlocal PDE Systems via Flow Map Learning

arXiv:2608.00400v1 Announce Type: new Abstract: Nonlocal partial differential equations arise in many applications but are often difficult to model and learn because of the presence of nonlocal operat

tutorialsarxiv-cs-lg

ORCA: ORgan-Centroid Aggregation for Training-Free 3D CT Visual Token Compression

arXiv:2608.00345v1 Announce Type: new Abstract: A 3D CT scan entering a vision-language model produces a long sequence of visual tokens, often thousands to tens of thousands per volume, and this seque

Pretrain on Small Synthetic Data, Scale Large for Free: Symmetry-Aware Foundation Model for Logic Rule Induction

arXiv:2608.00383v1 Announce Type: cross Abstract: Logical rule induction seeks interpretable rules that transfer across propositional schemas. This requires respecting symmetries: atom naming, example

RamanPFN: learning from Raman spectral structure with a tabular foundation model

model-releasesarxiv-cs-lg

arXiv:2608.02157v1 Announce Type: new Abstract: Raman spectroscopy enables non-destructive, label-free molecular characterization across materials science, biomedicine and process monitoring. Predicti

SafeBuild-Bench: A Temporal-Robust Construction Safety Benchmark with Graph-Enhanced Data Mining

arXiv:2608.00068v1 Announce Type: new Abstract: Construction-safety models must handle concrete deployment risks, such as a worker standing near a scaffold edge without guardrails, rather than only re

Semantic-Guided Cross-Sensor Super Resolution of Remote Sensing Images: A Gated Dual Conditioning Flow Matching Model

arXiv:2510.23816v3 Announce Type: replace Abstract: High spatial resolution satellite imagery is critical for monitoring fine-scale Earth surface processes, but is often limited by cost and revisit ti

Why LLMs Give In: Conversational Factors and Reasoning Behind Medical Sycophancy

arXiv:2608.01017v1 Announce Type: new Abstract: A language model that abandons a correct medical answer under user pushback is more dangerous than one that was simply wrong, because it lends the credi