Search: “papers”

Co-design of trajectory and morphology for a vertical jump-climbing robot

model-releasesarxiv-cs-ro

arXiv:2609.31014v1 Announce Type: new Abstract: Animals such as squirrels and even bears have adapted to rapidly climb up trees and other complex vertical terrain, but achieving comparable agility has

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Comparative Evaluation of an XR Pen-based Control Interface for Semi-Autonomous Mobile Robot Navigation in Service Environments

DGX agent

arXiv:2609.31117v1 Announce Type: new Abstract: Service robots remain difficult to deploy in domestic environments, partly because fully autonomous operation is not yet reliable in unpredictable surro

model-releasesarxiv-cs-ro

28 Sept 2026

Counterfactual Online Conformal Prediction Under Adaptive Logging

arXiv:2609.30811v1 Announce Type: new Abstract: Online conformal prediction can fail when predictions shape actions and actions determine which outcomes enter calibration. Standard adaptive methods ma

safetyarxiv-cs-lg

Different Corruptions, Different Signals: Uncertainty and Loss in Federated Data Quality

arXiv:2609.31454v1 Announce Type: cross Abstract: Federated learning (FL) data corruption can affect either inputs or labels, but it remains unclear whether input-conditional uncertainty and predictio

Differentiable RNA Secondary Structure Extraction for Deep Learning

arXiv:2609.30752v1 Announce Type: new Abstract: Many deep learning approaches to RNA secondary structure prediction have recently been proposed. They typically output a weight matrix W where W_{ij} is

Local Ai

Distributed Learning as a Service: The Developer's Perspective

arXiv:2609.31061v1 Announce Type: new Abstract: Application developers of distributed learning services face challenges that a typical federated learning loop does not address. Specifically, the model

local-aiarxiv-cs-lg

Does Uniform Discrete Diffusion Need Time?

arXiv:2609.30977v1 Announce Type: cross Abstract: Uniform discrete diffusion models (UDMs) commonly use explicit time conditioning, but we find that it can often be unnecessary in practice. In this pa

DynBranch: Speculative Subgraph Reuse for Dynamic Agentic LLM Serving

arXiv:2609.31047v1 Announce Type: cross Abstract: Agentic LLM workflows decide their execution paths at runtime. Downstream computation may be predictable, or may have run before, yet it cannot begin

agentsarxiv-cs-ai

Energy Efficiency of Locally Deployed LLMs: A Preliminary Quantitative GPU Power Benchmark on Consumer Hardware

arXiv:2608.00008v2 Announce Type: replace Abstract: The local deployment of large language models (LLMs) is gaining traction due to privacy concerns and the desire for on-premise inference. However, t

Equation discovery with Bayesian tree-adjoining grammars

arXiv:2609.31368v1 Announce Type: cross Abstract: Tree-Adjoining Grammars (TAGs) have recently been introduced to Nonlinear System Identification (NLSI) as a means of encoding an entire model class as

Fake News Theories: Harnessing Disciplinary Insights for Computational Modeling, Detection, and Explanation

arXiv:2609.30427v1 Announce Type: new Abstract: Disinformation research has produced increasingly accurate automated fake-news detectors, but many systems remain difficult to interpret and are weakly

Federated Targeted Maximum Likelihood Estimation

arXiv:2609.30503v1 Announce Type: new Abstract: The evidence behind a scientific or operational decision is often held by hospitals, banks, or registries that cannot pool individual observations. Cros

Forensic Twins: Self-Supervised Residual Learning for AI-Generated Image Forensics

arXiv:2609.31514v1 Announce Type: new Abstract: Detectors of AI-generated images are typically trained using samples from all Generative AI architectures they must catch, and struggle as soon as a new

researcharxiv-cs-cv

Frame the adversary: a structure-aware attack methodology

arXiv:2609.31128v1 Announce Type: new Abstract: Frequency-based adversarial attacks have recently grown popular by exploiting spectral sensitivities shared across neural architectures. Unlike spatial

safetyarxiv-cs-lg

From ASR to ASP: Evaluating Prompt Attack Vulnerabilities Against Open-Source LLMs

model-releasesarxiv-cs-cl

arXiv:2505.14368v3 Announce Type: replace-cross Abstract: Recent studies demonstrate that Large Language Models (LLMs) are vulnerable to attacks that generate harmful or sensitive outputs. As open-sou

Local Ai

G^2PTQ: Improving LLM Post-Training Quantization with Generalized Gradient Compensation

arXiv:2609.31009v1 Announce Type: cross Abstract: Post-training quantization (PTQ) is a practical approach to reducing the memory and computational footprint of large language models (LLMs) without re

local-aiarxiv-cs-ai

Gradient-Momentum Coupling: A Parameter-Space Proxy for Learning Progress

arXiv:2605.05856v2 Announce Type: replace Abstract: Measuring learning progress is at the core of curiosity-driven exploration, which rewards an agent for going where its model is still learning. Howe

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

Learning Chance-Constrained MDPs with Bellman Distributional Certificates

arXiv:2609.30856v1 Announce Type: new Abstract: Safe reinforcement learning (RL) commonly enforces expected-cost constraints, but such expectation safety may fail to control the probability of rare hi

LensDesigner: A Self-Improving Agent for Optical Lens Design

model-releasesarxiv-cs-cv

arXiv:2609.30450v1 Announce Type: new Abstract: Optical lens design is a complex, non-convex optimization challenge that relies heavily on human experience and intuition. Existing optimized-based auto

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

Tutorials

LLPR: Location-aware learning and physics-based reconstruction for raindrop removal from a single image

arXiv:2609.30758v1 Announce Type: new Abstract: Raindrops can cause occlusion and distortion in the background scenes due to their adherence to windows or camera lenses. Existing raindrop removal meth

tutorialsarxiv-cs-cv

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

Mentored Decoding: Faster Inference meets Boosting

arXiv:2609.30474v1 Announce Type: new Abstract: Speculative decoding is a successful technique speeding up inference of a target autoregressive language model via a fast drafter model. Lossy speculati

Models Got Talent: Identifying High Performing Wearable Human Activity Recognition Models Without Training

arXiv:2511.06157v3 Announce Type: replace-cross Abstract: Discovering high performing model architectures for wearables-based Human Activity Recognition (HAR) applications is challenging. The astonish

Applications

NavGen: Visual Generative Models as a Scalable Data Engine for Embodied 3D Navigation

arXiv:2609.30770v1 Announce Type: cross Abstract: General-purpose robot models increasingly rely on large and diverse datasets. For embodied 3D navigation, however, existing data sources face a fundam

applicationsarxiv-cs-ai

On associative neural networks for sparse patterns with huge capacities

arXiv:2603.26217v2 Announce Type: replace-cross Abstract: Generalized Hopfield models with higher-order or exponential interaction terms are known to have substantially larger storage capacities than

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

Parameter Estimation for Unnormalized Discrete Models via Empirically Localized Deformed Bregman Divergence

arXiv:2609.30713v1 Announce Type: cross Abstract: Estimation of parameter of probabilistic models is an important task in the field of machine learning.For models of discrete variables, calculation of

Parameters vs. Context: TRACE Fine-Tuning for Robust Retrieval-Augmented Generation

arXiv:2609.30337v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) mitigates knowledge obsolescence and factual hallucination in large language models by introducing external context

agentsarxiv-cs-lg

Preference-based opponent shaping in differentiable games

arXiv:2412.03072v2 Announce Type: replace Abstract: Strategy learning in game environments with multi-agent is a challenging problem. Since each agent's reward is determined by the joint strategy, a g

Privacy-Preserving Prompted Policy Search for Robotic Control

arXiv:2609.30554v1 Announce Type: new Abstract: Large language models (LLMs) have recently demonstrated promising capabilities as in-context policy optimizers for Reinforcement Learning (RL), enabling

safetyarxiv-cs-ro

Programs-of-Layers in LLMs through the Lens of Cortical Areas

arXiv:2609.31360v1 Announce Type: new Abstract: Inference in LLMs is conventionally a fixed-depth, fixed-order forward pass through every layer, regardless of how difficult the input is. The human bra

ReG-SAM: Reference Graph-Driven SAM for 2D Foundational Vessel Segmentation

arXiv:2609.31160v1 Announce Type: cross Abstract: Vessel segmentation in medical images is essential for many clinical tasks, ranging from diagnosis to treatment planning. However, it remains challeng

Applications

Retail Product Search: A Practical Approach at Target

arXiv:2609.31498v1 Announce Type: cross Abstract: Search is one of the most important features in e-commerce, directly driving customer engagement and business growth. A good product search system mus

applicationsarxiv-cs-lg

Scale-invariant Gaussian derivative residual networks

arXiv:2603.02843v2 Announce Type: replace Abstract: Generalisation across image scales remains a fundamental challenge for deep networks, which often fail to handle images at scales not seen during tr

researcharxiv-cs-cv

SEA-CLIP-Tiny: Efficient Multilingual Text-Vision Embedding for Southeast Asian Languages

arXiv:2609.30739v1 Announce Type: new Abstract: Multilingual text-vision embedding models are essential for cross-lingual image-text retrieval, but Southeast Asian languages remain poorly supported du

researcharxiv-cs-cl

Segment-Level Agentic Topic Modeling for Improved Data Exploration and Resource Efficiency

arXiv:2609.31460v1 Announce Type: new Abstract: Topic modeling is an effective technique for discovering hidden themes within documents and is widely used in text mining and data analysis across a var

agentsarxiv-cs-ai

Self-Supervised Perceptually Interpretable Monocular Depth Estimation

model-releasesarxiv-cs-cv

arXiv:2609.30987v1 Announce Type: new Abstract: Self-supervised monocular depth estimation (MDE) enables depth prediction from monocular images without requiring ground-truth supervision, making it at

Stealth Apart, Harm Together: Skill Cascading Attacks on Skill-Based Agent Systems

arXiv:2609.30383v1 Announce Type: new Abstract: A skill is a modular package of natural-language instructions, executable scripts, and reference resources that an agent can load at runtime to extend i

Stepwise Intrinsic Rewards for Reasoning in Large Language Models

arXiv:2602.01034v2 Announce Type: replace Abstract: Reinforcement learning (RL) has become a widely used paradigm for improving the reasoning abilities of large language models (LLMs) and Vision-langu

The Linear Representation Hypothesis for Vision-Language-Action Models

arXiv:2609.30996v1 Announce Type: cross Abstract: The linear representation hypothesis (LRH) has become a standard lens for measuring and intervening on semantic information through the internal repre

The Shrinking Lifespan of LLMs in Science

arXiv:2604.07530v3 Announce Type: replace-cross Abstract: Scaling laws describe how language model capabilities grow with compute and data, but say nothing about how long a model matters once released

Threat-Aware Energy-Efficient Deployment for Dynamic UAV Networks: A Multi-Agent RL Approach

arXiv:2609.30690v1 Announce Type: cross Abstract: Ensuring operational safety in threat-prone environments remains a critical challenge for multi-UAV networks serving as aerial base stations. This pap

Topology-Driven Anti-Entanglement Control for Soft Robots

arXiv:2605.05236v2 Announce Type: replace-cross Abstract: In the field of precision manufacturing in complex constrained environments, the role of soft robots is increasingly prominent, and the realiz

agentsarxiv-cs-ai

Towards Mitigating Fabricated Consensus: The Active Provenance Gate for Multi-Agent Debate Synthesis

arXiv:2609.31422v1 Announce Type: cross Abstract: Large language model-based multi-agent debate (MAD) systems are being increasingly used as complex decision pipelines in distributed processes. Howeve

Applications

Towards VLA-Dreamer: Refining VLA Behavior Using World Models

arXiv:2609.31313v1 Announce Type: cross Abstract: Vision-Language-Action models (VLAs), while showing strong potential for robot control, require massive amounts of high-quality imitation learning dat

applicationsarxiv-cs-ai