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arXiv:2609.31225v1 Announce Type: new Abstract: Contact-rich manipulation requires robots to balance accurate motion tracking with compliant interaction, yet most visual-action policies leave complian

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Research

Impedance Cloning: Learning Equilibrium Point Parameters for Contact-Rich Manipulation

DGX agent

arXiv:2609.30842v1 Announce Type: new Abstract: Contact-rich manipulation requires robots to regulate force against surfaces whose geometry deviates unpredictably from training conditions. Trajectory-

researcharxiv-cs-ro

28 Sept 2026

Improving Visual Sensitivity of LLMs on Multimodal Machine Translation with Metric-based Loss Weighting

arXiv:2609.31169v1 Announce Type: cross Abstract: Multimodal Machine Translation aims to incorporate additional signal from non-textual modalities to improve translations by resolving ambiguities. Whi

Insurance Reserve Intelligence Platform

arXiv:2609.30765v1 Announce Type: new Abstract: Insurance reserve estimation is a fundamental actuarial task supporting premium pricing, solvency assessment, financial reporting, capital planning, and

Intent2Tc: Automated Intent-to-Traffic Control Translation with Language Models

arXiv:2609.31397v1 Announce Type: cross Abstract: Automated and highly usable Quality-of-Service (QoS) enforcement requires translating high-level service intents into deployable traffic-management po

Interpretable-by-Design Descriptor Portfolios Match a 2048-Dimensional Foundation Embedding on Low-Data Molecular Assays

arXiv:2609.30789v1 Announce Type: new Abstract: In low-data structure-activity prediction, the choice of molecular representation can matter more than the choice of predictor, and tabular foundation m

Local Ai

Jagarin: A Three-Layer Architecture for Hibernating Personal Duty Agents on Mobile

arXiv:2603.05069v3 Announce Type: replace Abstract: Personal AI agents face a deployment paradox on mobile: persistent background execution drains the battery and conflicts with platform background li

local-aiarxiv-cs-ai

JevSoup: System-One Routing for Training-Free LoRA Composition

arXiv:2609.30922v1 Announce Type: new Abstract: Building adaptable AI systems requires effective coordination of specialized capabilities across diverse tasks. Low-rank adaptation (LoRA) enables modul

LadderMIL: Multiple Instance Learning with Coarse-to-Fine Self-Distillation

arXiv:2502.02707v5 Announce Type: replace Abstract: Multiple Instance Learning (MIL) for whole slide image (WSI) analysis in computational pathology often neglects instance-level learning as supervisi

researcharxiv-cs-cv

Latent Generative Solvers for Generalizable Long-Term Physics Simulation

arXiv:2602.11229v3 Announce Type: replace Abstract: Reliable physics simulation demands two capabilities that today's neural PDE solvers do not deliver together: generalization across heterogeneous PD

Learning Hierarchical Causal Representations of the Effects of Forcings on Temperature in Climate Models

arXiv:2609.30995v1 Announce Type: new Abstract: Machine learning (ML) emulators provide a fast and cost-effective method to simulate climate change scenarios after being trained on Earth System Models

Learning Robot Policies from Sparse Success Signals via STL-Guided Stein Variational Policy Gradient

arXiv:2609.31606v1 Announce Type: new Abstract: Learning robot policies for tasks with sparse success signals is challenging when completion depends on coordinated actions, precise contact outcomes, o

safetyarxiv-cs-ro

Learning to Bias: Machine Learning-Enhanced Particle Filters

arXiv:2609.30498v1 Announce Type: new Abstract: Sequential inference estimates latent states from noisy and incomplete observations. Particle Filters (PFs), a class of Monte Carlo methods based on imp

safetyarxiv-cs-lg

Learning to Leverage Compliance: A Policy-Admittance Learning Framework for Robotic Insertion

arXiv:2609.31439v1 Announce Type: new Abstract: Policy learning and compliant control offer a promising route to reliable autonomous assembly under pose errors and contact uncertainty. However, combin

safetyarxiv-cs-ro

Learning What to Skip: Counterfactual Credit Assignment for Efficient Multi-Agent LLM Workflows

arXiv:2609.30734v1 Announce Type: new Abstract: Multi-agent LLM workflows use planning, execution, verification, and summarization to improve task performance, yet the value of each component depends

LipSSM: Structurally Lipschitz-Bounded Cascaded State-Space Model via Metric Transfer between Consecutive SSM Layers

arXiv:2609.30973v1 Announce Type: new Abstract: Lipschitz continuity is a fundamental principle in the design of certifiably robust deep neural networks (DNNs), wherein adjusting the Lipschitz constan

Local Ai

LocUS: Head Selection and Subspace Projection for Targeted Activation Steering

arXiv:2609.31122v1 Announce Type: new Abstract: Activation steering is a powerful training-free paradigm for controlling large language models at inference time. However, standard approaches estimate

local-aiarxiv-cs-cl

Local Ai

LUMO (Lightweight Unified Multilingual Orchestrator): A Privacy Preserving Offline Voice Assistant

arXiv:2609.30692v1 Announce Type: new Abstract: Reliable voice interaction is essential in environments with limited internet connectivity and strong privacy. However, most existing voice assistants d

local-aiarxiv-cs-lg

MACBT: A Multi-Agent Cognitive Behavioral Therapy Decision Support System with Longitudinal Memory

arXiv:2609.30939v1 Announce Type: new Abstract: Cognitive behavioral therapy (CBT) is an evidence-based first-line treatment for depression, yet its scale is constrained by the time clinicians spend o

ManiVid: Unified and Explainable Forensic Analysis of Manipulated Videos

arXiv:2609.30934v1 Announce Type: new Abstract: Rapid advances in AI-generated video (AIGV) have increased the risks posed by deceptive video manipulation. Unlike fully synthetic videos, manipulated v

researcharxiv-cs-cv

MDSkin-Net: Multi-Task Skin Lesion Analysis Driven by Pattern Analysis Priors and Spatial Alignment Regularization

model-releasesarxiv-cs-cv

arXiv:2609.30855v1 Announce Type: new Abstract: Reliable skin lesion segmentation and classification are central to dermoscopic computer-aided diagnosis. Existing multi-task frameworks couple the two

Measurement and Potential Field-Based Patient Modeling for Model-Mediated Tele-ultrasound

arXiv:2509.15325v2 Announce Type: replace Abstract: Teleoperated ultrasound can improve diagnostic medical imaging access for remote communities. Having accurate force feedback is important for enabli

researcharxiv-cs-ro

MedTokenBudget: Lesion-Preserving Token Routing for Dermoscopic Image Classification

arXiv:2609.30613v1 Announce Type: cross Abstract: Dermoscopy classifiers built on Vision Transformers process all image patches uniformly, although diagnostic evidence is concentrated in the lesion re

Metacognitive Selective Ensemble for Mobile Systems

arXiv:2609.31031v1 Announce Type: new Abstract: Deep ensembles improve robustness in mobile sensing, but repeatedly executing many models over continuous sensor streams is costly. Selecting only a few

Modeling Student Sensemaking with LLMs and Knowledge-Graph-Guided Inference

arXiv:2609.31046v1 Announce Type: new Abstract: Collaborative science learning requires nuanced interpretation of student dialogue to characterize how learners identify knowledge gaps, build explanati

researcharxiv-cs-cl

Moment-guided edge sampling

arXiv:2609.30472v1 Announce Type: new Abstract: Edge sampling makes local decisions to achieve graph-level objectives, such as preserving structural properties. This creates a fundamental challenge: e

MoSAR: Mixture of Semantic Attention Regimes for Learning Adaptive and Approximable Attention Geometries

arXiv:2609.31261v1 Announce Type: cross Abstract: The quadratic complexity of dense self-attention remains a central bottleneck for long-context language modeling. Many efficient alternatives address

Applications

Motion Style Slider: Endpoint-Supervised Continuous Style Control for Human Motion Diffusion

arXiv:2609.30795v1 Announce Type: new Abstract: Existing human motion diffusion methods provide strong motion generation quality, and recent style transfer models can inject target style cues, but fin

applicationsarxiv-cs-cv

Mutable Transcripts: Mitigating Context Pollution through Editable Conversation State

arXiv:2609.31354v1 Announce Type: new Abstract: Contemporary large language model (LLM) chat systems treat conversation history as an immutable sequence of turns that defines the model's working conte

MVAgent: Multi-Agent Video Generation via Consistent Condition Construction and Shot-Level Policy Optimization

arXiv:2609.30609v1 Announce Type: new Abstract: Multi-shot agentic video generation requires consistent character appearance, stable spatial layout across camera angles, and continuous character state

safetyarxiv-cs-cv

MVVBench: Benchmarking 4D Reasoning in Vision-Language Models

arXiv:2609.30952v1 Announce Type: cross Abstract: Multi-view video understanding requires integrating spatial and temporal evidence across multiple, often non-overlapping camera streams: tracking enti

Neural Parameter Estimation of RC Thermal Building Models for Model Predictive Control

model-releasesarxiv-cs-lg

arXiv:2604.05904v2 Announce Type: replace-cross Abstract: Gray-box RC models are widely used to enable energy-efficient model predictive control (MPC) in buildings. However, estimating RC parameters r

NeuralCert: certified computational discovery of extremal mathematical constructions

arXiv:2609.30296v1 Announce Type: new Abstract: Neural networks are becoming popular in solving mathematical problems, but stochastic models do not provide mathematical exactness by themselves. This s

Neuralyzing the Trace: Selective Representation-Level Unlearning with Contrastive Sparse Autoencoders

arXiv:2609.31056v1 Announce Type: new Abstract: Machine unlearning aims to remove targeted information while preserving a model's other abilities. In realistic settings, such as privacy requests under

New LoRA Skills Should Read but Never Write

model-releasesarxiv-cs-lg

arXiv:2609.31600v1 Announce Type: new Abstract: Low-rank adapters (LoRA) make it cheap to fine-tune a large language model once per task, but combining several independently trained adapters into one

Not All Memories Are Equal: Hierarchical Collaborative Memory for Validity-Aware Retrieval in LLM Agents

arXiv:2609.30289v1 Announce Type: new Abstract: In team collaboration scenarios, memory is heterogeneous and continually evolving. Team memories capture collective decisions, protocols, and current co

researcharxiv-cs-cl

OC-GS: Gaussian Splatting for Irregular Turntable Capture

arXiv:2609.31572v1 Announce Type: cross Abstract: Uneven rotation and dropped frames make equal-angle assumptions unreliable for turntable reconstruction. We present OC-GS, an object-centric Gaussian

OmouAI: Argumentative Human-AI Policy Deliberation with Simulated Personas

arXiv:2609.31078v1 Announce Type: new Abstract: Debates amongst agents driven by large language models (LLMs) have demonstrated vast potential in various applications, but when these interactions incl

OneWorld: Learning Consistent Physics Across Actions in World Models

arXiv:2609.30946v1 Announce Type: cross Abstract: Action-conditioned video world models aim to predict scene evolution under different actions, a capability that is essential for reliable planning, de

Online Learning via Learned Latent Bayesian Tracking

model-releasesarxiv-cs-lg

arXiv:2609.31559v1 Announce Type: new Abstract: Online learning in non-stationary environments requires models to adapt rapidly from streaming data under strict computational constraints. A principled

OpenVAM: Open-World Visual Attention Modeling with VLMs

model-releasesarxiv-cs-cv

arXiv:2609.31364v1 Announce Type: new Abstract: Predicting human gaze is a core capability for applications ranging from web/UI design analysis to robotics and human-computer interaction. Yet, most vi

PALM: Point-in-Time Adaptation for Financial Language Models

model-releasesarxiv-cs-cl

arXiv:2609.30316v1 Announce Type: cross Abstract: Language models used in financial backtests suffer from look-ahead bias, as a model trained on text published after the study period has already obser

Peer-Grounded Counterfactual Path Planning for Chronic Health Management

arXiv:2609.30838v1 Announce Type: new Abstract: Effective behavioral intervention in chronic disease management requires not a single prescription but a sequence of incremental steps, each grounded in

Peer Review as Structured Commentary: Immutable Identity, Public Dialogue, and Reproducible Scholarship

arXiv:2506.22497v2 Announce Type: replace-cross Abstract: This paper reconceptualises peer review as structured public commentary. Traditional academic validation is hindered by anonymity, latency, an

PHASE: Compliance-Enabled Tactile Phase Retrieval for Few-Shot Insertion Learning

arXiv:2609.30889v1 Announce Type: new Abstract: Contact-rich assembly tasks such as peg-in-hole insertion remain difficult to learn from limited demonstrations. While retrieval-augmented imitation lea

safetyarxiv-cs-ro

PICO: Projection-Informed Consistency Optimisation for 6DoF Surgical Tool Pose Estimation

arXiv:2609.30989v1 Announce Type: new Abstract: Purpose: Accurate 6 DoF pose estimation of surgical tools is critical for automa- tion, robotic proprioception, and safe interaction with the tissue ope

researcharxiv-cs-cv

PORL: Pretrained Offline Reinforcement Learning for the Job Shop Scheduling Problem

arXiv:2609.30948v1 Announce Type: cross Abstract: The Job Shop Scheduling Problem (JSSP) is a fundamental combinatorial optimization problem in industrial optimization. This work introduces Pretrained

Applications

Precision at Speed: Sample-Efficient Online Model-Based Reinforcement Learning for Hydraulic Excavator Control

arXiv:2609.31025v1 Announce Type: cross Abstract: Precise, high-speed control remains challenging for robots with complex actuation dynamics. Learning directly on hardware is further constrained by th

applicationsarxiv-cs-lg