Search: “research”

Blind Dexterity: Whole-Body Humanoid Manipulation via Pure Proprioception

arXiv:2608.29487v1 Announce Type: new Abstract: We present blind, whole-body manipulation skills on a Unitree G1 humanoid using only onboard proprioception, without cameras, markers, force-torque, or

researcharxiv-cs-ro

Human

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Research

Blind Stereoscopic Omnidirectional Image Quality Assessment Using Predictive Coding Hierarchy

DGX agent

arXiv:2608.28798v1 Announce Type: new Abstract: Stereoscopic omnidirectional images (SOIs) have provided users with newly immersive quality of experience in virtual reality environments. However, deve

researcharxiv-cs-cv

1 Sept 2026

BlobBoards: Robust Markers for Accurate Pose

arXiv:2608.28830v1 Announce Type: new Abstract: We propose BlobBoards, a fiducial marker system comprising a dense, multi-scale field of Gaussian blobs and a feature-based pipeline for joint detection

Brain-Language-Action (BLA) Models: Language-Conditioned EEG for Robotics Control

arXiv:2608.28967v1 Announce Type: cross Abstract: Electroencephalography (EEG)-based robotic control is commonly formulated as a direct classification problem, in which electrical neural signals are m

BRF-GS: Hyperspectral Bidirectional Reflectance Factor Modeling and Image Generation Based on 3D Gaussian Splatting

arXiv:2608.31159v1 Announce Type: new Abstract: The bidirectional reflectance factor (BRF) characterizes the directional radiative properties of terrestrial surfaces. However, existing three-dimension

ButterMamba: Butterworth-Enhanced Spatial-Temporal Mamba for Efficient Traffic Flow Prediction

arXiv:2608.29658v1 Announce Type: cross Abstract: Accurate traffic flow prediction is fundamental to intelligent transportation systems, playing a pivotal role in urban mobility optimization and smart

Calibration and Comparative Analysis of Forward-Looking Sonar and 3D Sonar for Enhanced Underwater Object Recognition

arXiv:2608.29433v1 Announce Type: new Abstract: Sonars generate a significant amount of noise. With the advent of new technology capable of producing full 3D point clouds, the noise is amplified in sp

Camera trap classification with deep learning under ground truth uncertainty

arXiv:2608.30789v1 Announce Type: new Abstract: Supervised deep learning methods enable the rapid processing of ecological image data, but depend on a costly annotation process. Consequently, training

Can Large Language Models Identify Meaningful Touchpoints in Conversion Attribution?

arXiv:2608.28649v1 Announce Type: cross Abstract: Touchpoint selection in conversion attribution, namely identifying meaningful touchpoints contributing to conversions, is essential for e-commerce rec

Can Video World Models Track Unobserved World States?

arXiv:2608.30692v1 Announce Type: new Abstract: Video world models are increasingly used as simulators, yet visual fidelity alone does not show that a model maintains the hidden state of the world. We

CANVAS: Consistency-Aware Navigation via Visual Adaptive Sampling for Long-Context Text-to-SVG Generation

arXiv:2608.30689v1 Announce Type: new Abstract: Autoregressive large models have recently advanced Text-to-SVG generation from simple icons to complex, long-context graphics, yet standard autoregressi

Capability-Stratified Degradation in Ternary Language Models

arXiv:2608.28809v1 Announce Type: new Abstract: Extreme low-bit inference offers a route toward smaller models and constrained deployment. Ternary language models restrict weights to {-1,0,+1}, approa

CARVE: Verified Expansion for Variable-Length Generation in Diffusion Language Models

arXiv:2608.30922v1 Announce Type: new Abstract: Masked diffusion language models predict tokens from a partially observed response canvas, enabling bidirectional conditioning and parallel token refine

CateKV: On Sequential Consistency for Long-Context LLM Inference Acceleration

arXiv:2608.30295v1 Announce Type: cross Abstract: Large language models (LLMs) have demonstrated strong capabilities in handling long-context tasks, but processing such long contexts remains challengi

Causal Interventions Reveal Typologically Organized Syntactic Mechanisms in Multilingual Language Models

arXiv:2608.28924v1 Announce Type: new Abstract: Linguistic theory has long recognized cross-linguistic syntactic regularities, leading to claims that these similar structures are processed by similar

Centering before Pruning: Lightweight Geometry Correction for Diversity-Based Visual Token Pruning in LVLMs

arXiv:2608.30263v1 Announce Type: cross Abstract: Large vision-language models (LVLMs) incur substantial inference costs due to their long and highly redundant visual-token sequences. Diversity-based

CLIPure: Purification in Latent Space via CLIP for Adversarially Robust Zero-Shot Classification

arXiv:2502.18176v3 Announce Type: replace-cross Abstract: In this paper, we aim to build an adversarially robust zero-shot image classifier. We ground our work on CLIP, a vision-language pre-trained e

Clustering as Approximation by Constrained Projectors: Theory and Guarantees

arXiv:2608.29102v1 Announce Type: new Abstract: This paper develops a unified theoretical framework showing that a broad family of clustering methods, including k-means, fuzzy c-means, kernel k-means,

Co-Evolutionary Prompt Optimization with Cross-Category Transfer for Zero-Shot Anomaly Detection

arXiv:2608.29467v1 Announce Type: new Abstract: Zero-shot anomaly detection (ZSAD) has gained significant attention for its practical value in industrial inspection. Recently, CLIP-based approaches ha

Co-Evolving Actor-Conditioned Critics for Non-Verifiable Generation

arXiv:2608.30397v1 Announce Type: new Abstract: Natural-language critiques provide supervision beyond scalar rewards for non-verifiable generation, which lacks deterministic verifiers. In critique-gui

CoFiRec: Coarse-to-Fine Tokenization for Generative Recommendation

arXiv:2511.22707v2 Announce Type: replace-cross Abstract: In web environments, user preferences are often refined progressively as users move from browsing broad categories to exploring specific items

Model Releases

COGTRL: Training LLMs for Scientific Discovery Assistance using Cognitive Traces via Reinforcement Learning

model-releasesarxiv-cs-cl

arXiv:2608.30109v1 Announce Type: new Abstract: Large Language Models (LLMs) trained on extensive scientific research are increasingly integrated as assistants for scientific discovery. However, most

Compact and Infinite-Order Error Analysis for Null-Space SVD Estimation

arXiv:2608.30374v1 Announce Type: cross Abstract: We study null-space estimation from a noisy matrix. For a simple left null space, we first derive an exact compact expression for the error of the sma

Compact Snapshot Spectral Imaging with Calibration-Free Aperture Diffraction

arXiv:2608.29230v1 Announce Type: new Abstract: Snapshot Spectral Imaging (SSI) provides high-dimensional temporal-spatial-spectral observation to uncover intrinsic physical characteristics. However,

Configurable Semantic Chunking for Biomedical Information Extraction in Retrieval-Augmented Generation

arXiv:2608.31139v1 Announce Type: new Abstract: BioMedRAG introduced retrieval-augmented generation with a learned chunk scorer for biomedical information extraction. However, it relies on fixed-size

Conservative Hybrid Graph Networks for Process Systems with Learned Routing

arXiv:2608.28896v1 Announce Type: new Abstract: Industrial process networks do not maintain a single effective topology while operating: streams are throttled or bypassed, and units move between idle,

Constant Individual Regret in General Games

arXiv:2608.31166v1 Announce Type: new Abstract: Uncoupled no-regret dynamics provide a decentralized route to equilibrium, but prior guarantees for individual regret retain a polylogarithmic dependenc

Context-Aware Interleaved Batching for WhisperX

arXiv:2608.31170v1 Announce Type: new Abstract: While WhisperX accelerates speech transcription via intra-audio batching, it isolates audio segments, losing the historical context needed for coherent

Continual Test-Time Adaptation via Entropy Sensitivity-Guidance in Strict Online Setting

arXiv:2608.29920v1 Announce Type: new Abstract: Test-time adaptation (TTA) promises robustness under distribution shift by updating a pretrained model on unlabeled test data, but strict online TTA wit

Continuity-Free Near-Minimax Leading-Order Regret for CVaR-UCBVI

arXiv:2608.28960v1 Announce Type: new Abstract: For finite-horizon tabular CVaR reinforcement learning, prior work proves a widetilde{O}(au^{-1}sqrt{SAK}) leading regret bound for arbitrary normalized

Converse and Collision-Based Achievability for Node Localization with Hybrid Distance-Spectral Graph Positional Encodings

arXiv:2608.30152v1 Announce Type: new Abstract: Graph positional encodings are widely used in graph neural networks and graph Transformers, yet it remains unclear when the code itself can identify nod

Cost-efficient Active Learning for Referring Image Segmentation and Grounding

arXiv:2608.30621v1 Announce Type: cross Abstract: Collecting natural-language referring expressions along with region annotations, such as masks or boxes, is a major bottleneck in visual grounding (VG

CPR for LLMs: Critical-Point Routing against Catastrophic Forgetting in Domain Adaptation

arXiv:2608.30158v1 Announce Type: cross Abstract: Supervised fine-tuning (SFT) is the de facto standard for adapting large language models (LLMs) to target domains, but it often degrades the model's g

Cross-Regional Grapevine Cold Hardiness Prediction via Learned Multimodal Latent Representations

arXiv:2608.31097v1 Announce Type: new Abstract: Accurate daily predictions of cold hardiness in woody plants are critical in regions where freezing temperatures can damage dormant buds and reduce seas

Cross-Relational Preference Learning for Better LLM Instruction Following

arXiv:2608.29352v1 Announce Type: new Abstract: Large Language Models (LLMs) still exhibit limited capability in following complex instructions. While existing approaches often rely on preference lear

DARP: A Calibrated Dual-Arm RGB-D-IR Dataset for Multi-View Robotic Perception

arXiv:2608.31002v1 Announce Type: cross Abstract: Robotic perception from a single viewpoint is often limited by self-occlusion and incomplete surface visibility. This paper presents DARP(Dual-Arm Rob

DART: Draft-Agreement Routing for Training-Free Adaptive Thinking Budgets in Hybrid Reasoning Models

arXiv:2606.23181v2 Announce Type: replace Abstract: Hybrid reasoning models can answer directly or spend extra tokens on extended thinking. A practical router should choose between these modes for eac

Data Diversity, Not Frequency Invariance: A Controlled and Self-Audited Study of Compression-Robust Deepfake Detection

arXiv:2608.28685v1 Announce Type: new Abstract: Frequency features and compression-invariant representation learning are widely assumed to be key to deepfake detection that survives video compression.

Dataset Protection via Watermarked Canaries in Retrieval-Augmented LLMs

arXiv:2502.10673v2 Announce Type: replace-cross Abstract: Retrieval-Augmented Generation (RAG) has become an effective method for enhancing large language models (LLMs) with up-to-date knowledge. Howe

DesignAsCode: Bridging Structural Editability and Visual Fidelity in Graphic Design Generation

arXiv:2602.17690v3 Announce Type: replace-cross Abstract: Graphic design generation demands a delicate balance between high visual fidelity and fine-grained structural editability. However, existing a

DiffPDE: Masked Diffusion Language Models as PDE Solver

arXiv:2608.30532v1 Announce Type: new Abstract: Existing approaches for synthesizing Partial Differential Equation (PDE) solvers predominantly rely on autoregressive models, yet their global left-to-r

Diffusion-Based Inverse Design of Dielectric Resonator Metasurfaces for Shaping Smart Electromagnetic Environments

arXiv:2608.29907v1 Announce Type: new Abstract: Future wireless systems are expected to transform the surrounding space from a passive propagation medium into a smart electromagnetic environment, wher

DIP: Dynamic In-Context Planner For Diffusion Language Models

arXiv:2601.03199v2 Announce Type: replace-cross Abstract: Diffusion language models (DLMs) have shown strong potential for general natural language tasks with in-context examples. Existing In-Context

Disappearing Ink: Obfuscation Breaks N-gram Code Watermarks in Theory and Practice

arXiv:2507.05512v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly used for code generation, making reliable identification of machine-generated code important for

DisCo3D: Distilling Multi-View Consistency for 3D Scene Editing

arXiv:2508.01684v2 Announce Type: replace Abstract: While diffusion models have demonstrated remarkable progress in 2D image generation and editing, extending these capabilities to 3D editing remains

Distributed Semantic Segmentation With Improved Rate-Distortion Trade-Off

arXiv:2608.28684v1 Announce Type: new Abstract: Distributed deep neural networks (DNNs) for dense perception tasks such as semantic segmentation execute an encoder DNN on edge devices, and a decoder D

Do large language models scrutinise what they review? A multimodal audit of scoring calibration, error detection, and author-identity effects

arXiv:2608.28626v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used to generate peer reviews, prompting examination of their capacity for critical evaluation. This stu

Do LLMs Change Their Minds Like Humans? Diagnosing Human--LLM Divergence in Single-Turn Persuasion Judgments

arXiv:2608.29803v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed as proxies for human participants in social simulations, yet whether they update their beliefs