Search: “model-releases”

PC7 Model: Dynamics of Expanding and Contracting Soft Robots using Piece-wise Constant 7D Deformation Based on Similarity Transformation Group

arXiv:2610.14586v1 Announce Type: new Abstract: This paper proposes a novel soft robot model named piece-wise constant 7D deformation (PC7) model that can represent expanding and contracting deformati

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Personalized Physiological-Model-Based Neural Network for Glucose Forecasting in Type 1 Diabetes

arXiv:2610.15456v1 Announce Type: cross Abstract: Accurate, physiologically consistent glucose forecasts could help people with type 1 diabetes respond to impending excursions. We applied our physiolo

Pessimistic Latent Task-aware Optimization for Robust Offline Meta-Reinforcement Learning

arXiv:2610.15428v1 Announce Type: new Abstract: Context-based offline meta-reinforcement learning (COMRL) has advanced almost entirely through better task representations, which separate task identity

PGSB: Pretrained-Guided Shared Basis for LoRA Model Merging

arXiv:2610.14558v1 Announce Type: new Abstract: Large pretrained models have achieved remarkable success across diverse domains, yet adapting them to multiple downstream tasks remains challenging: ful

PhaseQuant: Mitigating Activation Quantization Collapse via Residual-Stream Dynamics

arXiv:2606.12487v2 Announce Type: replace Abstract: Post-training quantization (PTQ) is essential for efficient large language model (LLM) inference, but reliably quantizing activations remains challe

Physical-Field-Bridged Material Parameter Inference from Multi-View Deformation Videos

arXiv:2610.17591v1 Announce Type: new Abstract: Estimating simulation-ready material parameters from visual observations is crucial for deformable-object manipulation but challenging because material

Physical SLAM: Physics-aware Simultaneous Localisation and Mapping

arXiv:2610.17260v1 Announce Type: new Abstract: To reconstruct a predictive 4D representation of the physical world from monocular video captured by a moving camera, we jointly reconstruct dynamic Gau

Physics-guided machine learning for saturation control across variable hydraulic conditions in heap leaching

arXiv:2610.15947v1 Announce Type: cross Abstract: Heap-leaching hydraulics vary between regions of an ore bed, motivating fast prediction models that accommodate different material properties. This st

Physics-informed random neural architectures on compact boundaryless multiply connected manifolds for random-operator models in machine learning and uncertainty quantification

arXiv:2610.14844v1 Announce Type: cross Abstract: We introduce stochastic physics-informed neural networks (SPINNs) for stochastic boundary-value problems (SBVPs) with random operators. The method enf

PhysicsSliders: Learning Physical Controls for Audio Foley Generation

arXiv:2610.18597v1 Announce Type: cross Abstract: Physical properties provide intuitive controls for sounds made by interacting objects. The challenge is to make a generative model respond predictably

PhySimCode: A Benchmark and Evaluation Method for Physics Video to Code Generation

arXiv:2610.15722v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) are good at video understanding and code generation, but it remains unclear whether they can recover the physic

PID-Gated Continual Prompt Adaptation Under Noisy Feedback

arXiv:2610.16129v1 Announce Type: new Abstract: Deploying LLM agents in non-stationary environments requires continually revising their instructions as the task drifts, yet rewriting after every repor

PixelMoE: Scaling Pixel-Space Diffusion with LLM-Style Mixture-of-Experts

arXiv:2610.18857v1 Announce Type: new Abstract: Pixel-space diffusion models provide an appealing alternative to latent-space diffusion models by directly modeling raw images without relying on a lear

Plan-Bench: Can Existing VLMs Go Well Beyond Perception to Reason and Plan in Embodied Worlds?

arXiv:2610.18836v1 Announce Type: new Abstract: Vision-Language Models (VLMs) have achieved strong performance in visual perception and spatial reasoning, leading to growing interest in using them as

PLAYGROUND: Progressive Layout Generation with Render-Grounded Planning

arXiv:2610.18865v1 Announce Type: new Abstract: Generating editable graphic designs requires arranging visual and textual elements into a coherent composition while preserving their content and editab

PolUR: Polarization Aware Multimodal Degradation Perception for Underwater Image Restoration

arXiv:2610.17991v1 Announce Type: new Abstract: Recovering high-quality images from degraded underwater observations is crucial for underwater exploration. Polarization observations show promise as an

PotentialEP: Backprop-Free Training of CIFAR-Scale Generative Models via Equilibrium Propagation

arXiv:2610.14409v1 Announce Type: new Abstract: Generating an image with a diffusion or flow-matching model typically involves integrating a velocity field for hundreds of sequential steps. That compu

PRIME: Frequency-Aware Unified Pruning and Merging for MoE Compression

arXiv:2610.13982v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) models have emerged as an effective paradigm for scaling large language models, yet their massive parameter footprint poses sev

Privacy-Preserving GNN Inference on Financial Transaction Graphs via Homomorphic Encryption

arXiv:2610.18054v1 Announce Type: cross Abstract: Anti-money laundering (AML) in financial networks requires modeling transaction patterns that span multiple institutions. In practice, however, banks

ProbabilityBench: Model Evaluation and Calibration with Exact Ground-Truth Uncertainty

arXiv:2610.17016v1 Announce Type: new Abstract: Evaluating model uncertainty on real-world data is challenging because each instance provides only a single observed label, leaving true conditional cla

Probing and Inducing Clinical Modality Grounding in Brain Tumor Segmentation

arXiv:2603.19844v3 Announce Type: replace Abstract: Multimodal MRI provides complementary information for brain tumor segmentation, but high accuracy alone does not reveal whether a model relies on cl

ProML: Progressive Multi-label Learning

arXiv:2610.15614v1 Announce Type: new Abstract: Multi-label learning typically pursues model construction through the joint optimization of label fitting, correlation modeling, and structural regulari

ProTok: Unified Protein Tokenization via Modular Multi-Codebook Quantization

arXiv:2610.18481v1 Announce Type: new Abstract: Protein sequence, structure, and functional annotations each capture complementary aspects of protein biology, yet existing tokenizers encode each modal

PsyBer-Agent: A Psychology-Driven User Agent for Recommender Systems

arXiv:2610.13989v1 Announce Type: cross Abstract: Evaluating recommender systems before deployment requires simulators that remain realistic over long, closed-loop interaction cycles. Current LLM-base

PVFH-Bench: Benchmarking Premise-Induced Visual Fixation Hallucinations in Vision-Language Models

arXiv:2610.14635v1 Announce Type: cross Abstract: Large Vision-Language Models (LVLMs) have achieved remarkable progress across a wide range of multimodal tasks. However, object hallucination remains

Q-Save: Towards Scoring and Attribution for Generated Video Evaluation

arXiv:2511.18825v3 Announce Type: replace Abstract: Evaluating AI-generated video (AIGV) quality hinges on three crucial dimensions: visual quality, dynamic quality, and text-video alignment. While nu

QTrack: Query-Driven Reasoning for Multi-modal MOT

arXiv:2603.13759v2 Announce Type: replace Abstract: Category-level multi-object trackers estimate trajectories for all detected instances, whereas some applications require propagating only targets sp

Query-Adaptive Neuron Steering for LLMs

arXiv:2610.14519v1 Announce Type: new Abstract: Effectively eliciting the capabilities of large language models (LLMs) at inference time remains an important challenge. Existing studies address this c

RadarGSOcc: Doppler-Aware 3D Semantic Occupancy Prediction Using 4D Radar Tensor with Geometric-Semantic Feature Extraction

arXiv:2610.18686v1 Announce Type: new Abstract: 3D semantic occupancy prediction is crucial for autonomous driving, but camera-based methods degrade in low-light conditions and LiDAR-based methods are

RAIN: Robotic Task Generalization with Region-Aware Interaction Networks

arXiv:2610.14039v1 Announce Type: cross Abstract: Existing vision-language-action (VLA) models benefit from large-scale vision-language pretraining, but tend to memorize training trajectories, limitin

RAR: Rate-Adaptive Rollout for Time-Consistent Interactive World Models

arXiv:2610.16302v1 Announce Type: new Abstract: Video-based interactive world models aim to enable real-time, user-controllable environments. Yet most existing systems are trained and rolled out at a

Real-Time Traffic Density Estimation: A Hybrid Computer Vision and Predictive Machine Learning Pipeline

arXiv:2610.14326v1 Announce Type: new Abstract: Traffic density estimation from camera feeds requires connecting visual perception with short-horizon forecasting. We present a two-stage pipeline that

RealityBench: Simulated Environments to Evaluate a Vision Language Model's Ability to Document Human Physical Work

arXiv:2610.14397v1 Announce Type: new Abstract: Augmenting worker capabilities in the physical world through guidance has been a decades-long goal for AI agents. One key supporting capability is to un

Recasting DiT for Extreme Image Compression with Hierarchical Visual Priors

arXiv:2610.18607v1 Announce Type: new Abstract: Pretrained diffusion models provide powerful generative priors for extreme image compression, but their stochastic, iterative generation processes are n

Recurrent In-Context Learning for Tabular Foundation Models

arXiv:2610.14998v1 Announce Type: new Abstract: Tabular foundation models adapt to new datasets through in-context learning (ICL), and, like most transformers, they tie computational depth to the numb

Reference-Efficient Multimodal Bitstream-Corrupted Video Recovery via Depth-Conditioned Adaptation

arXiv:2610.15806v1 Announce Type: new Abstract: Recovering visually faithful content from damaged video bitstreams is important for reliable multimedia communication and storage. Existing methods expl

Reference Wording Shapes Retrieval of Robot Task Instructions

arXiv:2610.17549v1 Announce Type: cross Abstract: Identifying a robot task from a short instruction is sensitive to which descriptions are available for retrieval. We investigate this effect in the na

ReForesight: Occlusion-Robust Re-Identification and Future Occupancy Forecasting for Dynamic Semantic Mapping

arXiv:2610.17279v1 Announce Type: new Abstract: Robots sharing walkways need to know where people will be, yet semantic occupancy maps show only where they are. We present ReForesight, an open-source

Refuses in Chat, Complies with Arms: LLM Refusal Does Not Survive Robot Control

arXiv:2610.14043v1 Announce Type: cross Abstract: Frontier language models reliably refuse to explain how to cause physical harm. We ask whether this refusal survives when the same models control a ro

Reinforcement Learning In Partially Verifiable Environments for Colon Cancer Treatment Planning

arXiv:2610.17426v1 Announce Type: new Abstract: Clinical decision-making is a sequential process of information collection, clinical inference, and forecasting under partial observability, often witho

RELAGRAM: Recursive Latent Graph Model for the Capacitated Vehicle Routing Problem

arXiv:2610.15106v1 Announce Type: new Abstract: Latent recursion repeatedly processes internal representations through the same neural network. Recent work has shown this approach to be effective on s

Relational Learning as World Modeling

arXiv:2610.16763v1 Announce Type: new Abstract: Relational learning typically predicts from a database state, but decision making asks a different question: how will that state change under an action?

ReMAP: Lossless Residual Neural Lifting for Scalable MAP Inference in Arbitrary-Order Markov Random Fields

arXiv:2411.18954v5 Announce Type: replace Abstract: Maximum a posteriori inference in a finite Markov random field is generally NP-hard. We study an instance-wise optimizer that minimizes the exact mu

Remembering What Matters for Long-Horizon Robotic World Models

arXiv:2610.14583v1 Announce Type: cross Abstract: Autoregressive robot video world models based on discrete visual tokens remain unreliable over long rollout horizons. Retaining the entire generated h

RepProbe: Can Video Language Models Count Repeated Actions? A Diagnostic Benchmark

arXiv:2610.18844v1 Announce Type: new Abstract: Repetition counting requires identifying and enumerating action cycles over time. While state-of-the-art video language models describe actions fluently

Representation Drift in Continual Learning: LoRA versus N-gram Memory

arXiv:2610.14921v1 Announce Type: new Abstract: A language model that keeps learning online must not slowly erode its own base capabilities. We ask which part of a modern LLM should absorb continual u

RES-MR: Risk-Aware Reasoning for Explainable and Safe Medication Recommendation

arXiv:2610.14474v1 Announce Type: new Abstract: Medication recommendations seek to deliver personalized drug combinations based on patients' clinical information, where ensuring transparent decision-m

ReTerm: Recovery Training for Self-Improving Terminal Agents

arXiv:2610.18484v1 Announce Type: cross Abstract: Terminal agents have shown strong abilities in complex coding tasks. However, they often struggle to recover from errors during long-running execution