Search: “research”

Soft Curriculum Learning for Optimizing Fresh and Generalized Recommendations

arXiv:2609.35783v1 Announce Type: cross Abstract: Large-scale recommender systems, particularly short-form video platforms, are often bottlenecked by massive popularity feedback loops. In such environ

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Sparse cubical complexes for efficient topology-preservation in image data

DGX agent

arXiv:2609.37177v1 Announce Type: new Abstract: Persistent homology (PH) is a frequently used tool for extracting and preserving topological information from image data, particularly in image segmenta

researcharxiv-cs-cv

30 Sept 2026

Stealth Is a Relation, Not a Property: How Event Representations Create Blind Spots for Timing Attacks in Event-Based Perception

arXiv:2609.36386v1 Announce Type: new Abstract: An event camera produces an asynchronous stream, but what is visible in that stream depends on how a downstream consumer, such as a model or detector, p

Stein-based Optimization of Sampling Distributions in Model Predictive Path Integral Control

arXiv:2511.02015v3 Announce Type: replace Abstract: This paper introduces a method for Model Predictive Path Integral (MPPI) control that optimizes sample generation towards an optimal trajectory thro

researcharxiv-cs-ro

Stochastic Optimization Under Power-Law Spectra: Tight Bounds and Shuffling Analysis

arXiv:2609.36271v1 Announce Type: new Abstract: Recent work has established that power-law spectral conditions on data enable tight convergence bounds for deterministic gradient descent, resolving the

Strict-Saddle Landscapes and Multi-Rank Geometry in Low-Tubal-Rank Tensor Sensing

arXiv:2609.37865v1 Announce Type: new Abstract: We study the optimization landscape of low-tubal-rank tensor sensing through a balanced factorization. Under a tubal restricted isometry condition, we e

StructRL: Online Structured Reinforcement Learning for Long-Horizon Vision-Language-Action Tasks

arXiv:2609.36352v1 Announce Type: new Abstract: Vision-language-action (VLA) models perform well on shorter-horizon manipulation tasks but still struggle with long-horizon tasks that require multiple

Structured Visual Target Learning For Cross-Subject eeg-to-image retrieval

arXiv:2609.36971v1 Announce Type: new Abstract: Cross-subject EEG-to-image retrieval requires a neural represen- tation trained on source subjects to remain aligned with a visual embedding space for a

Support-Set Target Leakage in Relational Foundation Models during In-Context Learning: Impact, Detection, and Mitigation

arXiv:2609.36384v1 Announce Type: new Abstract: Relational in-context learning (ICL) conditions predictions on the labeled support examples and their linked tables, creating a failure mode when the su

Surgical Master Console Using General-Purpose Robot Arms and a Separable Articulated Distal Interface: Porcine In-Vivo Evaluation

arXiv:2609.37455v1 Announce Type: new Abstract: High-performance surgical master consoles offer intuitive articulated manipulation but are expensive and difficult to reproduce, while accessible commer

researcharxiv-cs-ro

Sycophancy Is Not One Thing: Causal Separation of Sycophantic Behaviors in LLMs

arXiv:2509.21305v4 Announce Type: replace Abstract: Large language models (LLMs) often exhibit sycophantic behaviors -- such as excessive agreement with or flattery of the user -- but it is unclear wh

Temporal-Aware Fusion for Robust Outdoor LiDAR Localization

arXiv:2609.36432v1 Announce Type: new Abstract: LiDAR relocalization aims to estimate the global 6-DoF pose of a sensor in the environment. However, existing regression-based approaches often encounte

Texture Space Material Diffusion

arXiv:2609.37654v1 Announce Type: new Abstract: We present a method for generating high quality materials for 3D objects entirely in texture space. We finetune a video diffusion transformer for text-g

The Default Trap: Rethinking Plan Evaluation in Tool-Using LLM Agents

arXiv:2609.36829v1 Announce Type: new Abstract: An executor can respond strongly to a change in a supplied plan's priority while showing a small change in the same information-selection probability wh

The Detectability Gap: Hidden Heterogeneity in Hallucination Detection Across Language Models

arXiv:2609.35860v1 Announce Type: cross Abstract: Sampling based consistency is widely used for hallucination detection, yet aggregate performance can conceal systematic differences in which errors ar

The finite-horizon five-expert prediction problem

arXiv:2609.38035v1 Announce Type: cross Abstract: We give an explicit solution to the five expert prediction with expert advice partial differential equation (PDE) in the finite-time horizon setting.

The Price of Token Boundaries: Compression Certificates and Prediction

arXiv:2609.35869v1 Announce Type: new Abstract: Pre-tokenisation restricts which text fragments can become prediction units, but its compression cost is obscured when tokenisers are compared only unde

The Signed Geometry of One-Shot Recourse: On-Path Validity and the Signed-Curvature Criterion

arXiv:2609.36252v1 Announce Type: new Abstract: Closed-form recourse moves a rejected user along the unit gradient hat g of the classifier score f by the promised distance d_p=|f(x)|/|nabla f(x)|, at

The Surge of Anti-Semitism in German Social Media following the October 7 Attacks

arXiv:2609.36290v1 Announce Type: cross Abstract: We investigate the extent to which the Hamas attacks on Israel of October 7, 2023, have affected German social media debates about Judaism and Israel.

The Universal Classifier for Graph Learning

arXiv:2609.36302v1 Announce Type: new Abstract: While foundation models have revolutionized natural language processing and computer vision by leveraging universal vocabularies, Graph Machine Learning

The Vote Hides the Failure: Aggregation Choice and Noise Robustness in Heart Murmur Detection

arXiv:2609.37161v1 Announce Type: new Abstract: Noise robustness in automated phonocardiogram (PCG) murmur detection, and how it is measured, remains underexamined despite growing interest in low-reso

Theory on Attention Dynamics for Out-of-Distribution In-Context Learning

arXiv:2609.36448v1 Announce Type: new Abstract: Transformers have demonstrated remarkable in-context learning (ICL) capabilities, enabling them to perform new tasks without additional fine-tuning. How

Time-Anchored Diffusion Language Models: Latent-Space Caching for Fast Generation

arXiv:2609.37924v1 Announce Type: cross Abstract: Recent work on anchored diffusion language models improves denoising by shaping an intermediate latent space with supervised important-token targets.

ToolFence: Fine-Grained Authorization for Secure Tool-Using LLM Agents

arXiv:2609.37196v1 Announce Type: cross Abstract: Tool-using LLM agents remain vulnerable to indirect prompt injection because trusted instructions and untrusted observations share one context, allowi

TopoEmbedX: A General Framework for Representation Learning on Topological Domains

arXiv:2609.37884v1 Announce Type: new Abstract: Topological structures such as simplicial complexes, hypergraphs, and cell complexes extend standard graph models by modeling higher-order relationships

Tracing the Evidence: Faithful Token Attribution Through Vision-Language Reasoning

arXiv:2609.37656v1 Announce Type: new Abstract: Large vision-language models (LVLMs) exhibit strong reasoning capabilities, yet the visual and textual evidence supporting the generated responses remai

Tracing the Evolution of Oracle Bone Characters Across Three Millennia

arXiv:2609.35674v2 Announce Type: replace Abstract: Of the approximately 4,500 Oracle Bone Inscription (OBI) characters discovered from the Shang dynasty, only about 1,600 have been deciphered. Many c

Training-Free Global Geometric Association for 4D LiDAR Panoptic Segmentation

arXiv:2512.18991v3 Announce Type: replace-cross Abstract: Dominant paradigms for 4D LiDAR panoptic segmentation are usually required to train deep neural networks with large superimposed point clouds

Transformers Stop Thinking Too Early, and a Tiny LoRA Fixes It

arXiv:2609.36585v1 Announce Type: new Abstract: Pretrained transformers use little of their depth to follow references in context. Thirteen base models reliably follow only 1.4-3.6 lines, and extra pr

Transversal Pooling Neural Networks

arXiv:2609.36237v1 Announce Type: new Abstract: Many learning tasks require stability to small transformations while retaining sensitivity to larger ones. We introduce transversal pooling neural netwo

TReVS: Integrating Textual Relevance and Visual Saliency for Efficient Vision-Language Model Token Pruning

arXiv:2609.37581v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) excel at visual understanding and reasoning but often incur substantial inference costs due to the large number of visua

TTMark: Pairwise Distortion-Free Watermarking Beyond Single-Token Entropy

arXiv:2609.36372v1 Announce Type: cross Abstract: Distortion-free watermarking enables reliable attribution of machine-generated text while preserving output distribution. However, existing methods op

UGO: Unified Architecture for General Multi-Object Tracking by Segmentation

arXiv:2609.37339v1 Announce Type: new Abstract: General multi-object tracking (GMOT) tracks all instances of a user-specified category from a single first-frame exemplar. Prior work relies on bounding

UltraMatch: Transport Path Routing for Ultra-Fast and Memory-Efficient Image Matching

arXiv:2609.36980v1 Announce Type: new Abstract: Despite recent advances in accuracy and efficiency, coarse matching remains an indispensable yet costly stage in existing semi-dense matchers due to den

Understanding Private Evolution as Learning-Augmented Clustering

arXiv:2609.36678v1 Announce Type: new Abstract: Private Evolution (PE) is a differentially private algorithm for synthetic data generation. While it can be viewed as a Wasserstein learning algorithm,

V-Engram: Trigger-Indexed External Memory for Modular Text-to-Image Personalization

arXiv:2609.37198v1 Announce Type: new Abstract: Pretrained text-to-image models contain broad visual knowledge, yet they cannot reliably acquire or refine a specific visual identity from only a few re

Variational Augmented Invertible Koopman Autoencoder for probabilistic time series forecasting

arXiv:2609.37435v1 Announce Type: new Abstract: Neural Koopman autoencoder models have been shown to successfully build a latent embedding with linear dynamics for arbitrary dynamical systems, enablin

Variational Mixtures and Multi-Marginal Flow Matching: Advancing Statistical Inference with Biological Applications

arXiv:2609.36911v1 Announce Type: new Abstract: In this thesis I develop methods for statistical inference when the distributions arising from complex biological systems are multi-modal, geometrically

VISTA: Value-Informed Event Appraisal for Multimodal Emotion Conflict

arXiv:2609.37324v1 Announce Type: new Abstract: Conflicting emotional cues can be individually valid: a subdued voice may reflect a blocked goal while a smile satisfies a social obligation. Their inte

Visual Branch is What You Need for CLIP-based Class-Incremental Learning

arXiv:2609.37888v1 Announce Type: new Abstract: Class-Incremental Learning (CIL) requires models to recognize new classes over time without forgetting previously learned ones. With the rise of vision-

VLM Fine-Tuning for End-to-End Combinatorial Optimization

arXiv:2609.37175v1 Announce Type: new Abstract: Large language models (LLMs) have provided a unified interface for end-to-end combinatorial optimization (CO), but textual serialization alone may obscu

Volatility-Clustering Adaptation for Financial Time Series

arXiv:2609.37715v1 Announce Type: new Abstract: Time-series foundation models are increasingly adapted to new domains through fine-tuning on target data, under the implicit assumption that more target

Watch-Think-Interact: Bootstrapping Long-Horizon Multi-Turn Streaming Video Reasoning with Reinforcement Learning

arXiv:2609.37035v1 Announce Type: new Abstract: Streaming video assistance requires models to answer asynchronous questions from an observed prefix under a fixed context budget. Existing approaches mo

What Makes High-Magnification Knowledge Transferable? A Study of Cross-Resolution Distillation in Whole-Slide Imaging

arXiv:2609.36407v1 Announce Type: new Abstract: Cross-resolution knowledge distillation aims to improve low-magnification whole- slide analysis by transferring high-magnification representations, yet

When Successful Memories Mislead Embodied Agents:Memory Adaption For Task-Conditioned Execution

arXiv:2609.35808v1 Announce Type: cross Abstract: Experience reuse can reduce repeated exploration in embodied agents, but a trajectory that succeeded previously may be unsuitable for the current exec

When Updating Stops Being Learning: Rethinking LLM Self-Evolution via learnable information gain

arXiv:2609.36535v1 Announce Type: new Abstract: Self-evolution lets large language models (LLMs) improve iteratively using their own generated data, but often suffers from self-evolution degeneration:

Why Backdooring Neural Networks is so Easy?

arXiv:2609.36117v1 Announce Type: new Abstract: Securing modern AI systems against backdoor attacks remains an open challenge and requires fundamentally principled estimates of the adversary's budget

WINGS: Reference-Free Gaussian Splatting Inpainting with 3D-Native Generative Priors

arXiv:2609.37816v1 Announce Type: new Abstract: Inpainting 3D Gaussian Splatting scenes, a key challenge in 3D editing, requires generating plausible content within a masked region of 3D space. Prior