Search: “papers”

ToDMA: Large Model-Driven Massive Token Communications for Semantic Multiple Access

arXiv:2505.10946v3 Announce Type: replace-cross Abstract: Token communications (TokenCom) is an emerging generative semantic communication paradigm, where tokens serve as compact representation units

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TriphiBot: A Triphibious Robot Combining FOC-based Propulsion with Eccentric Design

DGX agent

arXiv:2602.01385v2 Announce Type: replace Abstract: Triphibious robots capable of multi-domain motion and cross-domain transitions are promising to handle complex tasks across diverse environments. Ho

researcharxiv-cs-ro

10 Jul 2026

Hardware

TurboMap: GPU-Accelerated Local Mapping for Visual SLAM

arXiv:2511.02036v5 Announce Type: replace Abstract: In real-time Visual SLAM systems, local mapping must operate under strict latency constraints, as delays degrade map quality and increase the risk o

hardwarearxiv-cs-ro

Understanding and Mitigating the Video-Action Generalization Gap via Temporal Ratio

model-releasesarxiv-cs-cv

arXiv:2607.08127v1 Announce Type: new Abstract: Generative video foundation models exhibit strong compositional priors, yet world-action models (WAMs) and video-action models (VAMs) often lose these p

Unified Face Attack Detection via Fine-Grained Semantic Guidance

arXiv:2607.08156v1 Announce Type: new Abstract: The growing applications of facial recognition systems are accompanied by increasingly diverse security threats. Existing datasets lack detailed textual

safetyarxiv-cs-cv

Unit-Independent Low-Rate Wrist GSR Processing for Stress Detection Using Phasic nSCR Features

arXiv:2607.08007v1 Announce Type: cross Abstract: Galvanic skin response (GSR) is widely used for stress detection, but wrist-based GSR remains challenging because its absolute amplitude can differ su

Unveiling Public Opinion: A Study of Sentiment Analysis Using LSTM and Traditional Models

arXiv:2607.07772v1 Announce Type: new Abstract: In this age of social media, sites like Twitter have become meeting places for people to share their views and feelings on a wide range of issues and cu

researcharxiv-cs-cl

UtterTune: LoRA-Based Target-Language Pronunciation Edit and Control in Multilingual Text-to-Speech

arXiv:2508.09767v3 Announce Type: replace-cross Abstract: We propose UtterTune, a lightweight method for adapting a multilingual text-to-speech (TTS) system built on a large language model (LLM). It i

researcharxiv-cs-cl

Validating LLMs in social science: Epistemic threats and emerging norms

arXiv:2607.07915v1 Announce Type: cross Abstract: Large language models (LLMs) are reshaping social science methodology. Researchers increasingly prompt language models to generate quantitative measur

safetyarxiv-cs-cl

Vanilla SGD with Momentum Survives Heavy-Tailed Noise: Convergence Analysis without Gradient Clipping or Normalization

arXiv:2607.08104v1 Announce Type: new Abstract: Stochastic gradient descent (SGD) is a cornerstone of modern optimization. While its performance under heavy-tailed noise is often addressed through spe

Wat3R: Underwater 3D Geometry Learning without Annotations

arXiv:2607.08772v1 Announce Type: new Abstract: Estimating 3D geometry in underwater environments presents unique challenges due to light attenuation, scattering, and the absence of large-scale, high-

researcharxiv-cs-cv

Whareformer: Learning to Track What is Where in Long Egocentric Videos

arXiv:2607.08537v1 Announce Type: new Abstract: The recently established 'Out of Sight, Not out of Mind' (OSNOM) task for egocentric videos focuses on tracking objects that are moved by the camera wea

researcharxiv-cs-cv

Local Ai

Who Broke the System? Failure Localization in LLM-Based Multi-Agent Systems

arXiv:2607.07989v1 Announce Type: cross Abstract: Large language model (LLM) based multi-agent systems enable complex problem solving through coordinated reasoning and action, but their distributed st

local-aiarxiv-cs-ai

Workflow as Knowledge: Semantic Persistence for LLM-Mediated Workflows

arXiv:2607.08740v1 Announce Type: new Abstract: Large language model (LLM) applications increasingly use explicit workflows for tool use, retrieval, branching, checkpointing, and human approval. Exist

safetyarxiv-cs-ai

X-ACTA: eXtended Analytic Center Tension distribution Algorithm for fixed and mobile cable-driven-parallel-robot

arXiv:2607.08265v1 Announce Type: new Abstract: Steering Cable-Driven Parallel Robots (CDPRs) beyond their Wrench-Feasible Workspace (WFW) augments their capabilities in challenging scenarios such as

researcharxiv-cs-ro

A Distributionally Robust Optimisation Approach to Fair Credit Scoring

arXiv:2402.01811v2 Announce Type: replace Abstract: Credit scoring has been catalogued by the European Commission and the Executive Office of the US President as a high-risk classification task, in li

safetyarxiv-cs-lg

A Visual Introduction to Information Theory (bookmark it) Information Theory is such an beautiful and powerful subject. In the era of AI, it…

A Visual Introduction to Information Theory (bookmark it) Information Theory is such an beautiful and powerful subject. In the era of AI, it's worth spending time learning about it. Here is a highly-r

tutorialsdair-ai--x

Agents

Agent-Exploitation Affordances: From Basic to Complex Representation Patterns

arXiv:2607.07475v1 Announce Type: new Abstract: In robotics, the capability of an artificial agent to represent the range of its action possibilities, i.e. affordances, is crucial to understand how it

agentsarxiv-cs-ro

Local Ai

ALER-TI: Aligned Latent Embedding Retrieval for Time Series Imputation

arXiv:2607.07640v1 Announce Type: cross Abstract: Deep learning has significantly advanced time series imputation, yet most existing architectures primarily rely on localized temporal context within t

local-aiarxiv-cs-ai

Also this graph that shows what an 'AI-pilled' startup looks like, and how uncommon it is even among startups: the answer when founders are …

tutorialsethan-mollick--x

Also this graph that shows what an 'AI-pilled' startup looks like, and how uncommon it is even among startups: the answer when founders are asked 'Without GenAI, how many additional employees would yo

Can We Really Learn One Representation to Optimize All Rewards?

arXiv:2602.11399v2 Announce Type: replace-cross Abstract: As unsupervised pretraining becomes increasingly ubiquitous in reinforcement learning, a more thorough theoretical understanding of these meth

tutorialsarxiv-cs-ai

Computing with Stochastic Oracles in AI-Augmented Computation

arXiv:2607.06893v1 Announce Type: cross Abstract: The Stochastic-Oracle Turing Machine (SOTM) framework models AI-augmented computation as the interaction of a probabilistic Turing machine with an ora

Constrained Decoding for Diffusion Language Models via Efficient Inference over Finite Automata

arXiv:2607.07026v1 Announce Type: new Abstract: Constrained decoding is essential for serving LLMs, ensuring that generated outputs follow specific structures such as JSON schema-formatted function ca

Context-Aware Force Estimation for Deformable Tool Manipulation in Robotic Environmental Swabbing via Few-Shot Continual Adaptation

model-releasesarxiv-cs-ro

arXiv:2607.07574v1 Announce Type: new Abstract: Robotic surface swabbing requires sustained interaction between a compliant tool and heterogeneous environments, where accurate estimation of tip-level

Creating Power Distribution Network Layouts Using Generative Adversarial Networks and Image-Based Representations

arXiv:2607.06622v1 Announce Type: cross Abstract: Utilities increasingly rely on planning and operational tools to cope with the increased penetrations of distributed energy resources, yet the lack of

tutorialsarxiv-cs-lg

DiffCVE: Diffusion-based Compressed Video Enhancement

arXiv:2607.07195v1 Announce Type: new Abstract: Perceptual quality enhancement of severely compressed videos remains challenging due to complex artifact patterns and substantial information loss. Rece

researcharxiv-cs-cv

Discovering Geometric Biases in 3D Face Reconstruction: A Curvature-Aware Spectral Framework for Fairness Evaluation

arXiv:2607.07486v1 Announce Type: new Abstract: 3D Morphable Models (3DMMs) remain the standard parametric shape priors for many state-of-the-art 3D face reconstruction algorithms. However, as these m

safetyarxiv-cs-cv

Do Counterfactually Fair Image Classifiers Satisfy Group Fairness? -- A Theoretical and Empirical Study

arXiv:2607.06603v1 Announce Type: cross Abstract: The notion of algorithmic fairness has been actively explored from various aspects of fairness, such as counterfactual fairness (CF) and group fairnes

safetyarxiv-cs-ai

Agents

Effective Strategies for Asynchronous Software Engineering Agents

arXiv:2603.21489v2 Announce Type: replace-cross Abstract: AI agents have become increasingly capable at isolated software engineering (SWE) tasks such as resolving issues on Github. Yet long-horizon t

agentsarxiv-cs-ai

Evaluation of Multilingual Ability to Use Spatial Deictic Expressions in Vision-Language Models

model-releasesarxiv-cs-cl

arXiv:2607.07251v1 Announce Type: new Abstract: One of the expected abilities of vision-language models (VLMs) is spatial reasoning ability based on a given text and image. To evaluate the spatial rea

EvoPlan: Evolutionary Neuro-Symbolic Robot Planning with Spatio-Temporal Guarantees

model-releasesarxiv-cs-ro

arXiv:2607.06724v1 Announce Type: new Abstract: LLM-based robot planners are fluent but cannot guarantee that their plans are executable or safe. Classical PDDL planners can guarantee these properties

Explain Before You Answer: A Survey on Compositional Visual Reasoning

arXiv:2508.17298v3 Announce Type: replace-cross Abstract: Compositional visual reasoning has emerged as a key research frontier in multimodal AI, aiming to endow machines with the human-like ability t

Faster and Simpler Greedy Algorithm for k-Median and k-Means

arXiv:2407.11217v4 Announce Type: replace-cross Abstract: Clustering problems such as k-means and k-median are staples of unsupervised learning, and many algorithmic techniques have been developed to

FedCVESA: Taking Away Training Data in Federated Learning via Correlation Value Encoding and Segmented Aggregation

arXiv:2607.07314v1 Announce Type: cross Abstract: Federated learning (FL) avoids explicit data exposure by keeping raw data on local clients, yet privacy risks remain in the training process and the l

FMMVCC: Fuzzy Mamba-based Multi-View Contrastive Clustering for Univariate Time Series

arXiv:2607.07258v1 Announce Type: cross Abstract: In many realistic scenarios, large volumes of time series data are generated with limited or expensive annotations. This limitation makes supervised l

FPTQuant: Function-Preserving Transforms for LLM Quantization

arXiv:2506.04985v2 Announce Type: replace Abstract: Large language models (LLMs) require substantial compute, and thus energy, at inference time. While quantizing weights and activations is effective

From Content to Audience: A Multimodal Annotation Framework for Broadcast Television Analytics

arXiv:2603.26772v2 Announce Type: replace-cross Abstract: Automated semantic annotation of broadcast television content presents distinctive challenges, combining structured audiovisual composition, d

Applications

From Jumps to Signatures: a Generative Method for Temporal Point Processes

arXiv:2607.06652v1 Announce Type: new Abstract: Rough path signatures are a universal feature map for continuous paths and, via the expected signature, characterise path distributions. These guarantee

applicationsarxiv-cs-lg

From system models to class models: An in-context learning paradigm

arXiv:2308.13380v3 Announce Type: replace-cross Abstract: Is it possible to understand the intricacies of a dynamical system not solely from its input/output pattern, but also by observing the behavio

tutorialsarxiv-cs-lg

GemNav: Discrete-Token Visual Robot Navigation using a Multimodal Large Language Model

arXiv:2607.06882v1 Announce Type: cross Abstract: Visual navigation policies built on large pretrained models have so far followed a common recipe: a dedicated visual encoder, a bespoke action head, a

safetyarxiv-cs-ai

Generative Diffusion Models of Stochastic Graph Signals

arXiv:2607.06833v1 Announce Type: new Abstract: Sampling stochastic signals supported on a graph underlies many graph machine learning tasks, including recommender systems, forecasting in financial ma

tutorialsarxiv-cs-lg

Geometric--Nongeometric Optimizer Calculus: A Modular Language for Reachable Gradient Methods

model-releasesarxiv-cs-lg

arXiv:2607.07206v1 Announce Type: new Abstract: Adaptive optimizers mix several mechanisms: a metric or preconditioner maps gradients to descent directions, while estimation, memory, step-size control

HART: High-Resolution Annotation-Free Reasoning Technique through a Closed-loop Framework

arXiv:2602.23615v3 Announce Type: replace Abstract: Current Large Multimodal Models (LMMs) struggle with high-resolution visual inputs during the reasoning process, as the number of image tokens incre

safetyarxiv-cs-cv

Heterogeneity-Adaptive Diffusion Schrodinger Bridge for PET-Guided Whole-Body MRI Translation

arXiv:2607.07401v1 Announce Type: cross Abstract: While whole-body multimodal medical imaging scanners have been increasingly recognized for more effective medical applications, the excessive long acq

Hypergraph Neural Stochastic Diffusion: An SDE Framework for Uncertainty Estimation

arXiv:2607.07330v1 Announce Type: cross Abstract: Hypergraph neural networks have shown powerful capability in modeling higher-order relations, yet their predictive uncertainty remains underexplored.

Immersive Social Interaction with VR and LLM-Assisted Humanoids

arXiv:2607.07430v1 Announce Type: new Abstract: Humanoid robots can extend human presence to remote, constrained, or hazardous environments, but existing teleoperation interfaces often require physica

researcharxiv-cs-ro

Hardware

InferNet: Exploiting Aggregate GPU Profiles as Side-Channel for DNN Architecture Inference

arXiv:2304.03388v2 Announce Type: replace Abstract: Deep Neural Networks (DNNs) have become ubiquitous for their ability to solve problems across various domains, including computer vision, natural la

hardwarearxiv-cs-lg

Is Randomness Necessary for Adaptive Data Analysis?

arXiv:2607.07085v1 Announce Type: cross Abstract: The Adaptive Data Analysis (ADA) problem formalizes the challenge of preventing false discovery and overfitting when a dataset is repeatedly reused. F