Search: “research”

Graph Coloring for Multi-Task Learning

arXiv:2509.16959v5 Announce Type: replace-cross Abstract: When different objectives conflict with each other in multi-task learning, gradients begin to interfere and slow convergence, thereby potentia

GUI-AIMA: Aligning Intrinsic Multimodal Attention with a Context Anchor for GUI Grounding

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arXiv:2511.00810v4 Announce Type: replace-cross Abstract: Graphical user interface (GUI) grounding is a key capability for computer-use agents, mapping natural-language instructions to actionable regi

researcharxiv-cs-ai

1 Jul 2026

HABIT: Human-Aware Behavior and Interaction Training Dataset for Robot Manipulation

arXiv:2606.31682v1 Announce Type: new Abstract: Large-scale demonstration datasets have been central to recent progress in general-purpose robot policies. However, existing datasets are collected in h

researcharxiv-cs-ro

Hierarchical 3D Scene Graph Construction and Belief-based Planning for Semantic Navigation

arXiv:2606.31071v1 Announce Type: new Abstract: Semantic navigation is a fundamental task for embodied agents operating in unseen environments, requiring both semantic understanding and long-term deci

Hierarchical Clustering As a Novel Solution to the Notorious Multicollinearity Problem in Observational Causal Inference

arXiv:2606.30992v1 Announce Type: cross Abstract: Multicollinearity is a long lasting challenge in observational causal inference, especially in regressions -- highly correlated independent variables

How Can AI Find My Model? A Model-Finding Experimental Study Considering Data Formats, Embeddings, and Retrieval Strategies

arXiv:2606.30846v1 Announce Type: new Abstract: Discovering simulation models for reuse remains a fundamental challenge in Modeling and Simulation (M&S). When many models coexist, identifying those th

How (Not) to Hybridize Neural and Mechanistic Models for Epidemiological Forecasting

arXiv:2602.06323v2 Announce Type: replace Abstract: Epidemiological forecasting from surveillance data is a hard problem and hybridizing mechanistic compartmental models with neural models is a natura

How Post-Training Shapes Biological Reasoning Models

arXiv:2606.16517v2 Announce Type: replace Abstract: Scientific reasoning models for biology combine language models with foundation models trained on multimodal biological data, including DNA, RNA, an

Hybrid Unet-Transformer Model for Generating Stress and Strain Fields from Composite Geometrics

arXiv:2606.31068v1 Announce Type: new Abstract: Accurate prediction of stress and strain fields in hierarchical composite microstructures is critical for physics-informed material design, yet conventi

HyperVLP: Enhancing Hierarchical Surgical Video-Language Pre-training in Hyperbolic Space

arXiv:2606.31245v1 Announce Type: new Abstract: Surgical vision-language foundation models typically adopt educational materials, such as surgical lecture videos, to transfer surgical knowledge encode

Improved Upper Bounds for Slicing the Hypercube

arXiv:2602.16807v2 Announce Type: replace Abstract: A collection of hyperplanes H slices all edges of the n-dimensional hypercube Q_n with vertex set {-1,1}^n if, for every edge e in the hypercube, th

Improving Certified Robustness via Adversarial Distillation

arXiv:2606.31653v1 Announce Type: cross Abstract: Certified training aims to produce models whose predictions can be formally verified against adversarial perturbations, typically by optimising upper

Improving multichannel speech enhancement through accurate room-acoustic simulations

arXiv:2606.31552v1 Announce Type: cross Abstract: Room-acoustic simulations are widely used to augment training data for deep-learning-based speech enhancement. While most pipelines rely on simplified

Improving path-tracking performance of an articulated tractor-trailer system using a non-linear kinematic model

arXiv:2606.31889v1 Announce Type: new Abstract: This paper presents a novel non-linear mathematical model of an articulated tractor-trailer system that can be used, in combination with receding horizo

researcharxiv-cs-ro

Improving Survey Participation in Low-Literacy Populations Through Value-Sensitive Conversational AI

arXiv:2606.30660v1 Announce Type: cross Abstract: Collecting reliable social data from low-literacy populations remains a persistent challenge, particularly when surveys involve sensitive topics and m

In his SOTU speech in 2010, @barackobama warned that with it's Citizens United decision, the SCOTUS had 'opened the floodgates for special i…

In his SOTU speech in 2010, @barackobama warned that with it's Citizens United decision, the SCOTUS had 'opened the floodgates for special interests — including foreign corporations — to spend without

researchyann-lecun--x

InfoFlow KV: Information-Flow-Aware KV Recomputation for Long Context

arXiv:2603.05353v2 Announce Type: replace Abstract: Retrieval-augmented generation (RAG) for long-context question answering is bottlenecked by inference-time prefilling over large retrieved contexts.

Information Terra: A Narrative-Anchored Semantic-First Projection of Document Embeddings

arXiv:2606.30824v1 Announce Type: cross Abstract: We introduce Information Terra, a narrative-anchored semantic-first projection that places a document corpus on an Earth-like globe whose poles are tw

researcharxiv-cs-cl

Interface-Aware Neural Newton Preconditioning for Robust Cohesive Zone Model Simulations

arXiv:2606.31921v1 Announce Type: new Abstract: Cohesive Zone Models (CZMs) are widely used to simulate interface fracture, delamination, adhesive failure, and fiber--matrix debonding in aerospace com

Intrinsically Stable Spiking Neural Networks: Overcoming the Performance Barrier in the Absence of Batch Normalization

arXiv:2606.31695v1 Announce Type: new Abstract: The performance of deep spiking neural networks (SNNs) often relies on batch normalization (BN). However, the advanced dynamic BN variants used in state

Introduction to Stochastic Differential Equations for Generative Machine Learning: A Variational Perspective

arXiv:2606.31576v1 Announce Type: new Abstract: The use of ordinary and stochastic differential equations has led to substantial progress in generative machine learning with applications to, for examp

Is Natural Always Appropriate? Investigating Naturalness and Appropriateness Across Different Domains for TTS Evaluation

arXiv:2606.31729v1 Announce Type: cross Abstract: Text-to-speech (TTS) evaluation is an open challenge. While the primary target was 'naturalness,' recent fidelity gains shifted focus toward 'appropri

ISM:Self-Improving Strategy Memory for Continual Mathematical Reasoning

arXiv:2606.31191v1 Announce Type: new Abstract: We propose Intelligent Schema Memory (ISM), a self-evolving memory-augmented system that improves mathematical reasoning for a frozen LLM under continua

Joint Optimization for 4D Human-Scene Reconstruction in the Wild

arXiv:2501.02158v3 Announce Type: replace Abstract: Reconstructing human motion and its surrounding environment is crucial for understanding human-scene interaction and predicting human movements in t

LDHP: Library-Driven Hierarchical Planning for Non-prehensile Dexterous Manipulation

arXiv:2603.13844v2 Announce Type: replace Abstract: Non-prehensile manipulation is essential for handling thin, large, or otherwise ungraspable objects in unstructured settings. Prior planning and sea

researcharxiv-cs-ro

Learning a Sampling-Free Variational DNN Plugin from Tiny Training Sets to Refine OOD Segmentation With Uncertainty Estimation

arXiv:2606.15837v2 Announce Type: replace Abstract: Deep neural networks (DNNs) frequently fail to generalize to out-of-distribution (OOD) medical images because of variations in scanners and acquisit

Learning by Surprise: Adaptive Mitigation of Model Collapse in Large Language Models

arXiv:2410.12341v4 Announce Type: replace-cross Abstract: As AI-generated content increasingly populates the web, generative AI models are at growing risk of being trained on their own outputs, a proc

Learning Gaussian Graphical Models from a Glauber Trajectory Without Mixing

arXiv:2606.31230v1 Announce Type: new Abstract: We study the task of learning the structure of a d-sparse Gaussian graphical model on n variables from a single trajectory of Glauber dynamics. Beyond a

Learning to Select, Not Relearn: Hard-Routed Mixtures of Reasoning LoRAs

arXiv:2606.31413v1 Announce Type: new Abstract: Composing independently trained LoRA adapters into a single large language model is useful for multi-domain adaptation, especially when the original tra

LeCropFollow: Latent Space Planning for Navigation in Unstructured Crop Fields

arXiv:2606.31941v1 Announce Type: cross Abstract: Unstructured navigational features, such as irregular planting or discontinuities, remain the primary failure mode for under-canopy agricultural robot

LeWorld model becomes ADAPTIVE and meets MODEL-PREDICTIVE CONTROL AdaJEPA by Yann LeCun and colleagues performs actions, then checks the pre…

LeWorld model becomes ADAPTIVE and meets MODEL-PREDICTIVE CONTROL AdaJEPA by Yann LeCun and colleagues performs actions, then checks the predicted latent state versus the observed and adapts at TEST T

researchyann-lecun--x

Linguistic Distancing on Social Media: Indicators of Emotion Regulation Across Age Groups

arXiv:2606.30957v1 Announce Type: new Abstract: Managing our emotional responses to events is key to emotional well-being, a process referred to as emotion regulation in psychology. Previous work has

researcharxiv-cs-cl

Listening Between the Lines: Joint Learning of ASR Embeddings and LLM-Augmented Linguistics for Dementia Detection

arXiv:2606.30675v1 Announce Type: cross Abstract: Early detection of dementia through speech analysis offers a non-invasive screening alternative, but capturing both acoustic and linguistic biomarkers

LiteMatch: Lightweight Zero-Shot Stereo Matching via Cost Volume Stabilization

arXiv:2606.31636v1 Announce Type: new Abstract: Despite rapid progress in learning-based stereo matching, high accuracy is often achieved at the cost of heavy backbones and computationally intensive 3

LLM-Powered Interactive Robotic Action Synthesis from Multimodal Speech, Gestures, and Music

arXiv:2606.31158v1 Announce Type: cross Abstract: The quest for intuitive and natural human-robot interaction (HRI) remains a significant challenge in robotics. Traditional methods often rely on rigid

Localized Conformal Prediction for Image Classification with Vision-Language Models

arXiv:2606.31577v1 Announce Type: new Abstract: Conformal predictions have attracted significant attention in the field of uncertainty quantification, mainly because of their strong marginal coverage

LUMOS: A Semantic Operating-System Layer for Accessibility-Grounded AI Agents

arXiv:2606.30697v1 Announce Type: cross Abstract: Current operating systems expose interfaces optimized for human users but not for AI agents. Humans benefit from pixels, icons, windows, visual groupi

Machine Learning-based Feedback Linearization Control of Quadrotor Subject to Unmodeled Dynamics

arXiv:2606.31199v1 Announce Type: cross Abstract: The control of agile quadrotors in dynamic and uncertain environments remains an open area of investigation to this day, particularly when the complet

Making Sense of Touch from the Child's View for Contrastive Learning

arXiv:2606.31943v1 Announce Type: new Abstract: Is the sense of touch a mechanism for human babies' learning of visual concepts? If so, can we quantify its importance, and to what extent do babies rel

Mantis: Lightweight Foundation Model for Time Series Classification

arXiv:2502.15637v2 Announce Type: replace-cross Abstract: While foundation models have revolutionized various domains, their application to time series classification remains rather under-explored, wi

MAPE: Defending Against Transferable Adversarial Attacks Using Multi-Source Adversarial Perturbations Elimination

arXiv:2606.31378v1 Announce Type: new Abstract: Neural networks are vulnerable to meticulously crafted adversarial examples, leading to high-confidence misclassifications in image classification tasks

Mean-Field Model for Two-Layer Neural Networks Trained with Consensus-Based Optimization

arXiv:2511.21466v3 Announce Type: replace Abstract: We study Consensus-Based Optimization (CBO) for two-layer neural network training. We compare the performance of CBO against Adam on two test cases

Measuring Judgment Quality in Natural-Language Explanations: Evidence from Forecasting Tournaments

arXiv:2606.30987v1 Announce Type: new Abstract: Decision-makers routinely rely on expert judgments accompanied by written explanations, yet explanation quality is difficult to measure at scale. Foreca

researcharxiv-cs-cl

MediEncoder: Nonlinear Representation Learning for High-Dimensional Causal Mediation Analysis

arXiv:2606.30648v1 Announce Type: cross Abstract: Causal mediation analysis decomposes a treatment effect into indirect pathways through mediators and direct pathways not operating through them. Moder

Mesh BDF: Barycentric Dominance Field for 3D Native Mesh Generation

arXiv:2606.31777v1 Announce Type: new Abstract: Autoregressive (AR) modeling has recently achieved remarkable progress in native 3D mesh generation, largely due to its natural ability to handle variab

Minimizing Quantized Semantic Age of Information (QSAoI) in Foundation Model-Based Semantic Communications

arXiv:2606.31303v1 Announce Type: cross Abstract: The emerging techniques of semantic communications and edge computing in 6G networks necessitate a paradigm shift toward co-designed semantic-aware an

Mitigating Positional Leakage in 3D Masked Autoencoders for Robust Representation Learning

arXiv:2606.31570v1 Announce Type: cross Abstract: Masked autoencoding has emerged as a prominent paradigm for self-supervised learning on 3D point clouds, achieving competitive performance across down

Modal CEGAR-tableaux with RECAR and resolution-based SAT-shortcuts

arXiv:2606.31878v1 Announce Type: cross Abstract: We investigate two approaches for extending CEGAR-tableaux with SAT-shortcuts using a previously known approach called RECAR but also a totally new ap