research

Composing Linear Layers from Irreducibles

arXiv:2507.11688v4 Announce Type: replace Abstract: Contemporary large models often exhibit behaviors suggesting the presence of low-level primitives that compose into modules with richer functionalit

Consensus-based optimization (CBO): Towards Global Optimality in Robotics

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DGX agent

arXiv:2602.06868v2 Announce Type: replace Abstract: Zero-order optimization has recently received significant attention for designing optimal trajectories and policies for robotic systems. However, mo

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11 Jun 2026

Context-Driven Incremental Compression for Multi-Turn Dialogue Generation

arXiv:2606.12411v1 Announce Type: new Abstract: Modern conversational agents condition on an ever-growing dialogue history at each turn, incurring redundant attention and encoding costs that grow with

Continual Learning with Support Boundary Experience Blending

arXiv:2507.23534v3 Announce Type: replace-cross Abstract: Continual learning (CL) seeks to mitigate catastrophic forgetting when models are trained with sequential tasks. A common approach, experience

CountZES: Counting via Zero-Shot Exemplar Selection

arXiv:2512.16415v3 Announce Type: replace Abstract: Object counting in complex scenes is particularly challenging in the zero-shot (ZS) setting, where instances of unseen categories are counted using

CoVar: Confidence-Variance-Guided Pseudo-Label Selection for Semi-Supervised Learning

arXiv:2601.11670v3 Announce Type: replace-cross Abstract: Pseudo-label selection in semi-supervised learning is commonly driven by maximum-confidence thresholds, yet confidence alone can be unreliable

Cross-Domain Multi-Person Human Activity Recognition via Near-Field Wi-Fi Sensing

arXiv:2510.17816v2 Announce Type: replace-cross Abstract: Wi-Fi-based human activity recognition (HAR) provides substantial convenience and has emerged as a thriving research field, yet the coarse spa

Cross-Layer Discrete Concept Discovery for Interpreting Language Models

arXiv:2506.20040v3 Announce Type: replace-cross Abstract: Interpreting language models remains challenging due to the existence of residual stream, which linearly mixes and duplicates features across

CU-Multi: A Dataset for Multi-Robot Collaborative Perception

arXiv:2509.19463v2 Announce Type: replace Abstract: A central challenge for multi-robot systems is fusing independently gathered perception data into a unified representation. Despite progress in Coll

DarkVGGT: Seeing Through Darkness Using Thermal Geometry without Daylight Tax

arXiv:2606.11326v1 Announce Type: new Abstract: Recent feed-forward 3D reconstruction methods have demonstrated strong performance and flexibility in efficient end-to-end scene geometry estimation fro

Decoding Multimodal Cues: Unveiling the Implicit Meaning Behind Hateful Videos

arXiv:2606.11953v1 Announce Type: new Abstract: Hateful videos have become prevalent on online platforms, highlighting an urgent need for effective detection. However, existing studies primarily focus

Density estimation for Hellinger via minimum-distance estimators: mixtures of Gaussians, log-concave, and more

arXiv:2606.11469v1 Announce Type: cross Abstract: We study the task of density estimation, where we hope to accurately estimate a probability density from n samples. A textbook method for density esti

Detecting Sensitive Personal Information in Japanese Pre-Training Corpora for Large Language Models

arXiv:2606.12114v1 Announce Type: new Abstract: Sensitive personal information can appear in large-scale pre-training corpora for large language models (LLMs). Detecting and filtering such information

Doc-to-Atom: Learning to Compile and Compose Memory Atoms

arXiv:2606.12400v1 Announce Type: new Abstract: Long input sequences are central to document understanding and multi-step reasoning in Large Language Models, yet the quadratic cost of attention makes

Does the Question Really Matter? Training-Free Data Selection for Vision-Language SFT

arXiv:2603.09715v2 Announce Type: replace Abstract: Visual instruction tuning is crucial for improving vision-language large models (VLLMs). However, many samples can be solved via linguistic patterns

DynaTok: Token-Based 4D Reconstruction from Partial Point Clouds

arXiv:2606.12189v1 Announce Type: new Abstract: We address 4D reconstruction from partial point cloud sequences, where depth-sensor observations are incomplete, unordered, and lack explicit temporal c

ERN-Net : Evolving Reason Node-Net for Document Binarization

arXiv:2606.11710v1 Announce Type: new Abstract: This paper presents ERN-Net, an Evolving Reason Node-Net for efficient document image binarization. ERN-Net enhances degradation-sensitive regions, such

Evaluating and Combating the Impact of Concept Drift on the Performance of Machine Learning-Based Phishing Detection Systems

arXiv:2606.11471v1 Announce Type: cross Abstract: The expansion of the digital domain has resulted in a substantial increase in digital communication, with email emerging as one of the most prominent

EventRadar: Long-Range Visual UAV Discovery through Spatiotemporal Event Sensing

arXiv:2606.11285v1 Announce Type: new Abstract: Unauthorized unmanned aerial vehicle (UAV) activity around airports, public venues, and other sensitive sites has made protected-airspace monitoring inc

EvoLMM: Self-Evolving Large Multimodal Models with Continuous Rewards

arXiv:2511.16672v4 Announce Type: replace Abstract: Recent advances in large multimodal models (LMMs) have enabled impressive reasoning and perception abilities, yet most existing training pipelines s

Exploring Adaptive Masked Reconstruction for Self-Supervised Skeleton-Based Action Recognition

arXiv:2606.11450v1 Announce Type: new Abstract: Recently, masked skeleton reconstruction models have emerged as strong action representation learners, driving significant progress in self-supervised s

exttt{Range-Arithmetic}: Verifiable Deep Learning Inference on an Untrusted Party

arXiv:2505.17623v2 Announce Type: replace-cross Abstract: Verifiable computing (VC) has gained prominence in decentralized machine learning systems, where resource-intensive tasks like deep neural net

Factions Within, Uncertain Across: Within-Document Reader Sub-Groups in Social Highlighting

arXiv:2606.11613v1 Announce Type: cross Abstract: When many people highlight the same document, is the crowd a single consensus, or is it internally structured into reader sub-groups that mark differe

Family-Aware Residual Architecture for Predicting Quantum Circuit Simulation Performance

arXiv:2606.11620v1 Announce Type: cross Abstract: Approximate tensor-network simulators enable classical simulation of quantum circuits beyond the reach of exact methods, but selecting optimal approxi

Fast Speech Foundation Model Distillation Using Interleaved Stacking

arXiv:2606.11766v1 Announce Type: cross Abstract: Distilling a large speech foundation model (SFM) into an efficient student model has been successfully applied to low-resource environments. Although

Feature-Aligned Speech Watermarking for Robustness to Reconstruction Distortions

arXiv:2606.11828v1 Announce Type: cross Abstract: Audio watermarking aims to embed identifiable information into audio while remaining imperceptible. Existing methods adopt high-fidelity, low-energy d

Fibration Trees: A Unified Approach to Multi-Robot Motion Planning

arXiv:2606.12070v1 Announce Type: new Abstract: State space projections and decompositions have emerged as powerful tools to tackle the curse of dimensionality in high-dimensional, multi-robot motion

Finding Multiple Interpretations in Datasets

arXiv:2606.12277v1 Announce Type: new Abstract: In this paper, we propose an approach to finding sets of similar-performing models (in terms of loss/accuracy measurements) with highly different contex

Finding Sparse Subnetworks in One Training Cycle via Progressive Magnitude-Based Pruning

arXiv:2606.12278v1 Announce Type: new Abstract: Neural network pruning reduces model size by removing less important parameters while aiming to preserve predictive performance. Although the Lottery Ti

Findings of the MAGMaR 2026 Shared Task

arXiv:2606.12295v1 Announce Type: cross Abstract: This overview paper presents the results of the shared task for the second workshop on Multimodal Augmented Generation via Multimodal Retrieval (MAGMa

Flow Matching with In-Context Priors for Out-of-Distribution Brain Dynamics

arXiv:2606.11833v1 Announce Type: new Abstract: Flow matching and diffusion models enable conditional generation across domains ranging from images to proteins, with recent extensions to out-of-distri

FORT-Searcher: Synthesizing Shortcut-Resistant Search Tasks for Training Deep Search Agents

arXiv:2606.12087v1 Announce Type: new Abstract: Training deep search agents requires verifiable questions whose answers remain unavailable until sufficient evidence has been acquired through search. E

From 2D Grids to 1D Tokens: Reforming Shared Representations for Multimodal Image Fusion

arXiv:2606.12303v1 Announce Type: new Abstract: Multimodal image fusion aims to integrate complementary information from different modalities into a fused image that preserves rich local details while

From Persistence to Survival: Hypothesis Testing, Effect Sizes and Vectorisation for Topological Features

arXiv:2606.11911v1 Announce Type: cross Abstract: Persistence diagrams are common representations in topological data analysis, but they do not naturally live in a vector space, and the statistical to

From Prompts to Tokens: Internalizing Causal Supervision in Vision-Language Model for Multi-Image Causal Reasoning

arXiv:2606.11745v1 Announce Type: cross Abstract: Visual causal reasoning is essential for understanding and intervening in the physical world, requiring identification of causal variables from visual

Frozen Multimodal Embeddings for Personality and Cognitive Ability Assessment in Asynchronous Video Interviews

arXiv:2606.11930v1 Announce Type: cross Abstract: Predicting psychological traits from asynchronous video interviews (AVIs) is a challenging multimodal learning problem because labeled datasets are li

Generalization Hacking: Models Can Game Reinforcement Learning by Preventing Behavioral Generalization

arXiv:2606.12016v1 Announce Type: cross Abstract: Model post-training, and in particular reinforcement learning (RL), is one of the primary mechanisms by which developers can shape models' values and

Geometric Metrics and LLMs: What They Measure and When They Work

arXiv:2509.25359v2 Announce Type: replace-cross Abstract: We present a systematic stress-test of geometric metrics for LLM evaluation. Rank-based geometric properties of internal representations have

Geometry of Reason: Spectral Signatures of Valid Mathematical Reasoning

arXiv:2601.00791v2 Announce Type: replace-cross Abstract: Verifying whether a language model is genuinely reasoning or pattern-matching remains an open problem: learned verifiers are expensive, and ou

Gumbel-BEARD: Automatic Layer Selection for Self-Supervised Adaptation of Whisper in Low-Resource Domains

arXiv:2606.11429v1 Announce Type: cross Abstract: Speech foundation models often struggle in low-resource domains due to domain mismatch and data scarcity. We propose Gumbel-BEARD, a domain adaptation

Harness In-Context Operator Learning with Chain of Operators

arXiv:2606.12318v1 Announce Type: cross Abstract: Neural operators approximate mappings between function spaces, but often generalize poorly to other operators and usually require fine-tuning or retra

Hierarchical Probabilistic Conformal Prediction for Distributed Energy Resources Adoption

arXiv:2411.12193v4 Announce Type: replace-cross Abstract: The rapid growth of distributed energy resources (DERs) presents both opportunities and operational challenges for electric grid management. A

Higher order PCA-like rotation-invariant features for detailed shape descriptors modulo rotation

arXiv:2601.03326v2 Announce Type: replace Abstract: PCA can be used for rotation invariant features, describing a shape with its p_{ab}=E[(x_i-E[x_a])(x_b-E[x_b])] covariance matrix approximating shap

Human-Guided Co-Manipulation of Carbon Fiber Plies

arXiv:2606.11818v1 Announce Type: new Abstract: The handling of flexible materials is a difficult task to fully automate due to the challenges caused by the deformability of these types of objects. Me

Image Quality Assessment of Identity Cards Using Measures from Open Face Image Quality

arXiv:2606.11884v1 Announce Type: new Abstract: This paper addresses the challenge of assessing image quality in ID cards in remote verification systems by applying capture-related quality measures fr

iPack: Intuitive Bin Packing with Large Language Models

arXiv:2503.08445v2 Announce Type: replace Abstract: Robotics and automation are increasingly influential in logistics but remain largely confined to traditional warehouses. In grocery retail, advancem

Irresponsible AI: big tech's influence on AI research and associated impacts

arXiv:2512.03077v2 Announce Type: replace-cross Abstract: The accelerated development, deployment and adoption of artificial intelligence systems has been fuelled by the increasing presence of big tec

Judging Against the Reference: Uncovering Knowledge-Driven Failures in LLM-Judges on QA Evaluation

arXiv:2601.07506v2 Announce Type: replace Abstract: While large language models (LLMs) are increasingly used as automatic judges for question answering (QA) and other reference-conditioned evaluation