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arXiv:2506.11585v3 Announce Type: replace Abstract: We introduce OV-MAP, a novel approach to open-world 3D mapping for mobile robots by integrating open-features into 3D maps to enhance object recogni

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PAANI : On Device Visual Evidence Fusion and Explainable Guidance for River Robot Simulation

DGX agent

arXiv:2609.22353v1 Announce Type: new Abstract: Mobile river monitoring robots must interpret obstacles and water boundaries that geographic waypoints alone cannot describe. On resource constrained pl

local-aiarxiv-cs-ai

23 Sept 2026

PACE-dLLM: Elastic Block Decoding via Confidence Cliff Estimation for Diffusion Language Models

arXiv:2609.26249v1 Announce Type: new Abstract: Diffusion language models (dLLMs), such as LLaDA and Dream, have become competitive with autoregressive (AR) LLMs in generation quality while supporting

researcharxiv-cs-cl

PACT: From Credit Assignment to Critic Alignment

arXiv:2609.26355v1 Announce Type: new Abstract: Reinforcement learning has become a central component of large language model (LLM) post-training, yet token-level credit lacks a generally accepted mat

safetyarxiv-cs-lg

PAKT: Physically-Aligned Kinesthetic Teaching for Reinforcement Learning

arXiv:2609.25630v1 Announce Type: new Abstract: Real-world reinforcement learning (RL) systems still struggle with the demands of contact-rich industrial manipulation, including micrometer-level preci

Parameterized Dense-Sparse Fusion for Hybrid Retrieval: Tuning a Rank-Score Mix on BEIR SciFact with Qdrant

model-releasesarxiv-cs-ai

arXiv:2609.22770v2 Announce Type: cross Abstract: We study a parameterized hybrid ranker that fuses a dense embedding list and a sparse lexical list. The method has a small, explicit parameter vector:

PARTE: Plane-Assisted Robust Transformation Estimation for Point Cloud Registration

arXiv:2609.25375v1 Announce Type: new Abstract: Global point-cloud registration remains challenging when limited overlap, repetitive geometry, and sensor noise produce correspondence sets dominated by

researcharxiv-cs-ro

Partially Observed Sparse Graphs: The Unknown Sampling Rate is a Tail Index

arXiv:2609.26199v1 Announce Type: new Abstract: A large graph is often available only in part: a crawl stopped by its budget, a panel, a partial dump. When the sampled fraction s is known by design th

PartLLM: A Unified Multimodal Foundation for 3D Part Segmentation

arXiv:2609.25832v1 Announce Type: new Abstract: Part segmentation is a fundamental problem in computer graphics and 3D vision. Recent works have expanded 3D part segmentation beyond fixed taxonomies,

Partner-Specific Affective Precision in Social Active Inference

arXiv:2609.24876v1 Announce Type: new Abstract: In multi-agent social settings, model reliability varies across relationships. Beyond inferring what others will do, an agent must calibrate how confide

local-aiarxiv-cs-ai

Passes Alone, Fails Together: Benchmarking Semantic Coordination in Parallel LLM-Agent Development

arXiv:2609.25396v1 Announce Type: new Abstract: Parallel coding agents can produce patches that work alone but fail when merged. This happens when one agent changes an interface or rule that another a

PatchKV: Efficient KV Cache Recovery for Dynamically Edited LLM Contexts

arXiv:2609.26219v1 Announce Type: cross Abstract: Long-running LLM agent workflows often revise interior context spans while retaining long suffixes. Although suffix tokens remain unchanged, altered c

local-aiarxiv-cs-lg

Peerify: Benchmarking Peer-Review Claim Verification

arXiv:2609.25046v1 Announce Type: new Abstract: Peer review plays a central role in scholarly publishing, yet verifying whether reviewer claims are supported by manuscript evidence remains a largely m

Penalized Nonreversible Langevin for Constrained Sampling

arXiv:2609.25381v1 Announce Type: cross Abstract: We propose penalized nonreversible Langevin algorithms for sampling from pi(x)propto e^{-f(x)}mathbf 1_{mathcal C}(x), where mathcal Csubsetmathbb R^d

PermuFormer: Multi-Task Pretraining for Permutation Representation in Algebraic Combinatorics

arXiv:2609.25438v1 Announce Type: new Abstract: Diverse pretraining has been shown to be an effective method for learning reusable, domain-aware representations that provide a starting point for fine-

PERSONAWEAVER: Controllable Diversity Beyond Conventional Archetypes in Procedural Character Generation

arXiv:2609.26629v1 Announce Type: new Abstract: Procedural character generation aims to populate games, simulations, and other virtual worlds with diverse characters. Large language models (LLMs) offe

researcharxiv-cs-cl

phi-RIE: From Photorealistic Reconstruction to Interactive Environments

model-releasesarxiv-cs-ro

arXiv:2609.26795v1 Announce Type: new Abstract: 3D Gaussian Splatting (3DGS) can reconstruct a captured scene photorealistically, but the resulting representation does not by itself support physical i

PhysAI-Bench: A Benchmark for LLM-Based Agentic Decision-Making in Autonomous UAV-Centric Physical AI

model-releasesarxiv-cs-ai

arXiv:2609.23695v1 Announce Type: new Abstract: Recent advances in Physical AI have accelerated the use of foundation models in autonomous systems such as unmanned aerial vehicles (UAVs), which must p

Physics-guided deep metric learning with continuous time embeddings for open-world radar pulse de-interleaving

arXiv:2609.25057v1 Announce Type: cross Abstract: Radar pulse de-interleaving is a foundational Electronic Support Measures (ESM) task that aims to separate chronologically interleaved pulse streams f

PhyVisGen: Physically and Visually High-Fidelity Robotic Manipulation Data Generation

arXiv:2609.25653v1 Announce Type: new Abstract: Large-scale manipulation demonstrations are essential for learning robust visuomotor policies, yet real-world data collection is expensive and difficult

PINNForge: Execution-Grounded Evolutionary Design of Physics-Informed Neural Networks for PDE Solving via Large Language Models

arXiv:2609.23023v1 Announce Type: new Abstract: Physics-informed neural networks (PINNs) require coordinated choices over network representation, sampling, loss construction, and optimization, while e

researcharxiv-cs-ai

Pinocchio: Fast Uncertainty Estimates for Black-Box Language Models

arXiv:2609.24881v2 Announce Type: new Abstract: In high-stakes decision-making applications of large language models (LLMs), practitioners require not only accurate LLMs but also uncertainty estimates

researcharxiv-cs-ai

PLAT: Sparse Timed Keyframe Motion Tracking for Humanoid Control via Privileged Latent Transition Learning

arXiv:2609.25754v1 Announce Type: new Abstract: Humanoid motion tracking policies rely on dense frame-by-frame references, limiting their use as high-level motion controllers for planning and interact

Point Diffusion Mamba: Unified Diffusion-State-Space Modeling for Single-View 3D Reconstruction under Data Scarcity

arXiv:2609.25538v1 Announce Type: new Abstract: While single-view 3D reconstruction has seen significant progress, extrapolating complex 3D structures from inherently ambiguous 2D observations remains

Polyak-Type Extragradient Methods for Monotone Root-Finding Problems

arXiv:2609.26581v1 Announce Type: cross Abstract: We study Polyak-type step-size selection for extragradient methods for solving deterministic and stochastic monotone root-finding problems. We show th

Polynomial Scaling is Possible For Neural Operator Approximations of Structured Families of BSDEs

arXiv:2410.14788v4 Announce Type: replace-cross Abstract: Neural operator (NO) architectures learn nonlinear maps between infinite-dimensional function spaces and are widely used to accelerate simulat

safetyarxiv-cs-lg

PP-Net: A Hybrid Physical-Prior Neural Network for Scattered Light Removal in Biomedical Images on Embedded Devices

arXiv:2609.26474v1 Announce Type: cross Abstract: Scattered light is common in biomedical images, yet its removal remains challenging. The difficulty arises from three aspects: first, aligned scattere

Predict Before You Step: Auditable Occupancy Forecasting for Dynamic Obstacle Avoidance under Sparse Guidance

arXiv:2609.25969v1 Announce Type: new Abstract: Legged robots under sparse waypoint guidance must avoid moving obstacles using partial, rapidly changing LiDAR observations. We present LOOP (Latent-rec

Applications

Predicting Postprandial Glycemic Response from Meal Images, Clinical Variables, and Gut Microbiome Information

arXiv:2609.24453v1 Announce Type: new Abstract: Predicting postprandial glycemic response (PPGR) is fundamental to personalized nutrition and type 2 diabetes management, yet existing approaches typica

applicationsarxiv-cs-ai

Predictive Uncertainty for Neural CAE Surrogates

arXiv:2609.25430v1 Announce Type: new Abstract: Neural surrogates can substantially accelerate computer-aided engineering (CAE) workflows, but their use in design requires uncertainty estimates that r

PreGS: A Parameter-Transfer-Based Multi-Expert Graph Neural Network for Node Classification

arXiv:2609.26310v1 Announce Type: new Abstract: Graph neural networks have achieved strong performance in node classification by aggregating information from graph neighborhoods. However, a single agg

Pretraining of Medical Visual Encoders Toward Multi-modal Large Language Models

arXiv:2609.23860v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) commonly reuse visual encoders pretrained with CLIP, although the features of these ViTs are ultimately consume

local-aiarxiv-cs-ai

PreUnlearn: Auditing Collateral Knowledge Damage Before Large Language Model Unlearning

arXiv:2606.18473v2 Announce Type: replace Abstract: Machine unlearning for large language models (LLMs) aims to remove specified knowledge while preserving the rest of the model's capabilities. Howeve

researcharxiv-cs-cl

Probabilistic Modeling of Jailbreak on Multimodal LLMs: From Quantification to Application

model-releasesarxiv-cs-cv

arXiv:2503.06989v5 Announce Type: replace-cross Abstract: Recently, Multimodal Large Language Models (MLLMs) have demonstrated their superior ability in understanding multimodal content. However, they

ProcessLight: Process Supervision for Large Language Model Based Traffic Signal Control

arXiv:2609.22746v1 Announce Type: new Abstract: Large Language Models (LLMs) have recently been introduced into traffic signal control (TSC) as decision agents due to their strengths in human-readable

safetyarxiv-cs-ai

Prompt Breadth and Rollout Refresh Interact in On-Policy Distillation

arXiv:2609.25048v1 Announce Type: new Abstract: How many prompts does on-policy distillation (OPD) need, and how does the answer depend on the student policies that generate its training responses? We

safetyarxiv-cs-cl

PROSWIN: Probabilistic Solar Wind Speed Forecasting Using Deep Distributional Regression From Solar Images

arXiv:2609.26683v1 Announce Type: cross Abstract: Accurately predicting fast solar wind conditions is challenging, as uncertainties are large and unquantified by traditional single-value prediction mo

Protocol before progress: leakage-aware evaluation of AIS trajectory prediction

arXiv:2609.25827v1 Announce Type: new Abstract: Reported gains in vessel-trajectory prediction from Automatic Identification System (AIS) data are credited to new architectures, but the evaluation pro

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

Applications

Quantum Model Parallelism for MRI-Based Classification of Alzheimer's Disease Stages

arXiv:2602.00128v2 Announce Type: replace Abstract: With increasing life expectancy, AD has become a major global health concern. While classical AI-based methods have been developed for early diagnos

applicationsarxiv-cs-lg

QuantWM: Temporally Consistent 2-Bit KV Cache Quantization for World Models and Video Generation

arXiv:2609.26425v2 Announce Type: new Abstract: KV cache memory has become a major deployment bottleneck for video generation and world models, which motivates low-bit quantization study for efficienc

Qwen-Audio-3.1-Realtime: Towards Reliable Agentic Voice Interaction

arXiv:2609.25176v1 Announce Type: cross Abstract: Real-time voice assistants must reason over evolving requests, execute actions, and follow conversational rules. Qwen-Audio-3.1-Realtime brings these

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

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

Radiomics--Foundation Fusion for Interpretable RCC Classification: Internal Benchmarking and Exploratory External Transfer

arXiv:2609.26578v1 Announce Type: new Abstract: Accurate preoperative subtype classification of renal cell carcinoma (RCC) from contrast-enhanced CT remains clinically challenging because clear cell R

Radiomics-Conditioned Modulation of RenalCLIP Features for Clear Cell Renal Cell Carcinoma Classification

arXiv:2609.26492v1 Announce Type: new Abstract: Radiomics provides quantitative descriptions of tumour appearance that may complement disease-specific foundation models in small labelled cohorts. We i

RankCert: When Can Simulated Learners Safely Select an AI Tutor? Robust Decision Certification Under Structural Uncertainty

arXiv:2609.26069v1 Announce Type: cross Abstract: Simulation-based tutor selection can be unstable when predictively adequate learner models imply different policy rankings. RankCert certifies one of

Tutorials

Reading Right, Answering Wrong: How Visual Configuration Changes Affect Evidence Use in VLMs

arXiv:2609.25770v1 Announce Type: new Abstract: Vision-language models (VLMs) have achieved strong performance on tasks such as visual question answering, yet small image resizes can turn correct answ

tutorialsarxiv-cs-cv

Real-Time Atomic-Resolution Electron Phase Imaging without Probe Calibration via Ptychography-Supervised Learning

arXiv:2609.25684v1 Announce Type: new Abstract: Atomic-scale phase imaging is central to resolving defects, interfaces, and weakly scattering atoms that govern the behavior of nanoscale materials. Ele

local-aiarxiv-cs-cv