Search: “papers”

WorldPlay2: Extending Real-Time Interactive World Models in Control and Horizon

arXiv:2609.35560v1 Announce Type: new Abstract: Interactive world models require responding in real time to versatile controls and maintaining long-horizon consistency. However, modeling heterogeneous

researcharxiv-cs-cv

29 Sept 2026

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Model Releases

ZeroGAR: Benchmarking the Adversarial Robustness of Zero-Shot Graph Models

DGX agent

arXiv:2609.33314v1 Announce Type: new Abstract: Zero-shot graph models (ZGMs), which learn transferable knowledge from source graphs and directly apply to unseen target graphs without any adaptation,

model-releasesarxiv-cs-lg

29 Sept 2026

A Benchmark Framework for Screening Automation in Systematic Reviews

model-releasesarxiv-cs-cl

arXiv:2609.30298v1 Announce Type: new Abstract: Systematic reviews (SR) are essential for evidence-based research, but their screening phase is highly time-consuming and labor-intensive. Large languag

A Synthetic Ground-Truth Framework for the Evaluation of Explainable AI Methods

arXiv:2609.30397v1 Announce Type: new Abstract: Evaluating explainable Artificial Intelligence (XAI) methods is a challenging task due to the lack of reliable evaluation procedures and, in particular,

Tutorials

A Unified Account of Concepts and Chunks

arXiv:2609.30414v1 Announce Type: cross Abstract: Cognitive psychology has studied how people encode, use, and learn concepts that describe categories, and how they represent, recognize, and acquire c

tutorialsarxiv-cs-ai

Accuracy Evaluation of INS/ZUPT Filtering Methods Based on Different Geometric Error Definitions

arXiv:2609.31057v1 Announce Type: new Abstract: Geometric filters have recently been introduced to improve the accuracy and consistency of inertial-based integrated navigation systems. Error states we

researcharxiv-cs-ro

Amplify What You Gaze At: Target Saliency Boosting in Text-to-Image Generation

arXiv:2609.30733v1 Announce Type: new Abstract: Text-to-image generation has advanced in controlling what, where, and how objects appear, yet how visual attention is distributed among objects remains

safetyarxiv-cs-cv

Anchor to Expand: Semantic Anchoring for Personalized Text-to-Image Diffusion Models

arXiv:2511.22245v2 Announce Type: replace Abstract: Personalizing text-to-image diffusion models extends pretrained models to represent novel user-specific concepts from only a few reference images. H

safetyarxiv-cs-cv

Attention-Based Adaptive Policies for Simultaneous Speech-to-Text Translation

arXiv:2609.30839v1 Announce Type: new Abstract: Simultaneous speech-to-text translation (Simul-S2TT) consists of generating partial translations while the incoming audio frames are processed by the sy

safetyarxiv-cs-lg

Audio LLMs Know When They Can't Hear You

arXiv:2609.30625v1 Announce Type: new Abstract: Audio large language models allow users to interact with the model through speech. When an input recording is too degraded, the model may misinterpret t

safetyarxiv-cs-ai

AuthGuard-R: Safety-Compliant Mission Hijacking and Dual-Gate Defense for LLM-Controlled Robots

model-releasesarxiv-cs-ro

arXiv:2609.31110v1 Announce Type: new Abstract: Large language models are increasingly used as high-level planners for mobile robots, robot manipulators, and autonomous vehicles. Recent studies show t

AYLA: Amplifying Gradient Sensitivity via Loss Transformation in Non-Convex Optimization

arXiv:2504.01875v3 Announce Type: replace Abstract: Stochastic Gradient Descent (SGD) and its variants, such as ADAM, are foundational to deep learning optimization, adjusting model parameters through

Benchmarking the Connectomes of Caenorhabditis elegans within the Reservoir Computing Framework

arXiv:2609.30508v1 Announce Type: new Abstract: The aim of this work is to examine the connectomes of Caenorhabditis elegans through a computational lens using the reservoir computing framework. Conne

Benchy: towards a universal language for task-oriented AI benchmarks

arXiv:2609.30550v1 Announce Type: new Abstract: Benchy is a semantic language and execution engine for benchmarking AI programs. A benchmark is completely specified by a program, a scoring function, a

CCRV-Bench: Constraint-Based Evaluation of Causal Reasoning in Vision-Language Models

model-releasesarxiv-cs-cv

arXiv:2609.30979v1 Announce Type: new Abstract: Vision-language models (VLMs) have demonstrated excellent performance in visual tasks, but their visual causal reasoning capabilities still lack reliabl

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

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

model-releasesarxiv-cs-ro

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

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

Agents

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

safetyarxiv-cs-ai

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

Agents

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