Search: “concepts”

New Hybrid Fine-Tuning Paradigm for LLMs: Algorithm Design and Convergence Analysis Framework

arXiv:2604.09940v1 Announce Type: new Abstract: Fine-tuning Large Language Models (LLMs) typically involves either full fine-tuning, which updates all model parameters, or Parameter-Efficient Fine-Tun

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On the Effectiveness of Textual Prompting with Lightweight Fine-Tuning for SAM3 Remote Sensing Segmentation

DGX agent

arXiv:2512.15564v2 Announce Type: replace Abstract: Remote sensing (RS) image segmentation is constrained by the limited availability of annotated data and a gap between overhead imagery and natural i

safetyarxiv-cs-cv

14 Apr 2026

Performance Characterization of Frequency-Selective Wireless Power Transfer Toward Scalable Untethered Magnetic Actuation

arXiv:2604.11645v1 Announce Type: cross Abstract: Frequency-selective wireless power transfer provides a feasible route to enable independent actuation and control of multiple untethered robots in a c

researcharxiv-cs-ro

PrefPaint: Enhancing Medical Image Inpainting through Expert Human Feedback

arXiv:2506.21834v2 Announce Type: replace Abstract: Inpainting, the process of filling missing or corrupted image parts, has broad applications in medical imaging. However, generating anatomically acc

RoboCOIN: An Open-Sourced Bimanual Robotic Data Collection for Integrated Manipulation

arXiv:2511.17441v3 Announce Type: replace Abstract: Despite the critical role of bimanual manipulation in endowing robots with human-like dexterity, large-scale and diverse datasets remain scarce due

researcharxiv-cs-ro

Sat2Sound: A Unified Framework for Zero-Shot Soundscape Mapping

arXiv:2505.13777v2 Announce Type: replace-cross Abstract: We present Sat2Sound, a unified multimodal framework for geospatial soundscape understanding, designed to predict and map the distribution of

SCITUNE: Aligning Large Language Models with Human-Curated Scientific Multimodal Instructions

arXiv:2307.01139v2 Announce Type: replace-cross Abstract: Instruction finetuning is a popular paradigm to align large language models (LLM) with human intent. Despite its popularity, this idea is less

Hardware

SCNO: Spiking Compositional Neural Operator -- Towards a Neuromorphic Foundation Model for Nuclear PDE Solving

arXiv:2604.11625v1 Announce Type: cross Abstract: Neural operators have emerged as powerful surrogates for partial differential equation (PDE) solvers, yet they are typically trained as monolithic mod

hardwarearxiv-cs-ai

Tutorials

Smart Paste: Automatically Fixing Copy/Paste for Google Developers

arXiv:2510.03843v4 Announce Type: replace-cross Abstract: Manually editing pasted code is a long-standing developer pain point. In internal software development at Google, we observe that code is past

tutorialsarxiv-cs-lg

Tracing the Roots: A Multi-Agent Framework for Uncovering Data Lineage in Post-Training LLMs

arXiv:2604.10480v1 Announce Type: new Abstract: Post-training data plays a pivotal role in shaping the capabilities of Large Language Models (LLMs), yet datasets are often treated as isolated artifact

Hardware

VTC: DNN Compilation with Virtual Tensors for Data Movement Elimination

arXiv:2604.09558v1 Announce Type: cross Abstract: With the widening gap between compute and memory operation latencies, data movement optimizations have become increasingly important for DNN compilati

hardwarearxiv-cs-lg

Applications

WiFlow: A Lightweight WiFi-based Continuous Human Pose Estimation Network with Spatio-Temporal Feature Decoupling

arXiv:2602.08661v2 Announce Type: replace Abstract: Human pose estimation is fundamental to intelligent perception in the Internet of Things (IoT), enabling applications ranging from smart healthcare

applicationsarxiv-cs-cv

Zero-Shot Synthetic-to-Real Handwritten Text Recognition via Task Analogies

arXiv:2604.09713v1 Announce Type: new Abstract: Handwritten Text Recognition (HTR) models trained on synthetic handwriting often struggle to generalize to real text, and existing adaptation methods st

Demystifying the Silence of Correctness Bugs in PyTorch Compiler

arXiv:2604.08720v1 Announce Type: cross Abstract: Performance optimization of AI infrastructure is key to the fast adoption of large language models (LLMs). The PyTorch compiler (torch.compile), a cor

EmoCtrl: Controllable Emotional Image Content Generation

arXiv:2512.22437v2 Announce Type: replace Abstract: An image conveys meaning through both its visual content and emotional tone, jointly shaping human perception. We introduce Controllable Emotional I

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Applications

Investigating Multimodal Large Language Models to Support Usability Evaluation

arXiv:2508.16165v2 Announce Type: replace-cross Abstract: Usability evaluation is an essential method to support the design of effective and intuitive user interfaces (UIs). However, it commonly relie

applicationsarxiv-cs-ai

Local Ai

Offline-First LLM Architecture for Adaptive Learning in Low-Connectivity Environments

arXiv:2603.03339v5 Announce Type: replace-cross Abstract: Artificial intelligence (AI) and large language models (LLMs) are transforming educational technology by enabling conversational tutoring, per

local-aiarxiv-cs-cl

Overstating Attitudes, Ignoring Networks: LLM Biases in Simulating Misinformation Susceptibility

arXiv:2602.04674v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly used as proxies for human judgment in computational social science, yet their ability to reprodu

Region-Constrained Group Relative Policy Optimization for Flow-Based Image Editing

arXiv:2604.09386v1 Announce Type: new Abstract: Instruction-guided image editing requires balancing target modification with non-target preservation. Recently, flow-based models have emerged as a stro

safetyarxiv-cs-cv

Revisiting Anisotropy in Language Transformers: The Geometry of Learning Dynamics

arXiv:2604.08764v1 Announce Type: new Abstract: Since their introduction, Transformer architectures have dominated Natural Language Processing (NLP). However, recent research has highlighted an inhere

researcharxiv-cs-cl

SessionIntentBench: A Multi-task Inter-session Intention-shift Modeling Benchmark for E-commerce Customer Behavior Understanding

model-releasesarxiv-cs-cl

arXiv:2507.20185v2 Announce Type: replace Abstract: Session history is a common way of recording user interacting behaviors throughout a browsing activity with multiple products. For example, if an us

Agents

A Soft Robotic Interface for Chick-Robot Affective Interactions

arXiv:2604.08443v1 Announce Type: new Abstract: The potential of Animal-Robot Interaction (ARI) in welfare applications depends on how much an animal perceives a robotic agent as socially relevant, no

agentsarxiv-cs-ro

Alloc-MoE: Budget-Aware Expert Activation Allocation for Efficient Mixture-of-Experts Inference

model-releasesarxiv-cs-cl

arXiv:2604.08133v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) has become a dominant architecture for scaling large language models due to their sparse activation mechanism. However, the s

AnomalyVFM -- Transforming Vision Foundation Models into Zero-Shot Anomaly Detectors

arXiv:2601.20524v2 Announce Type: replace Abstract: Zero-shot anomaly detection aims to detect and localise abnormal regions in the image without access to any in-domain training images. While recent

AV-SQL: Decomposing Complex Text-to-SQL Queries with Agentic Views

arXiv:2604.07041v1 Announce Type: cross Abstract: Text-to-SQL is the task of translating natural language queries into executable SQL for a given database, enabling non-expert users to access structur

Between Century and Poet: Graph-Based Lexical Semantic Change in Persian Poetry

arXiv:2604.06674v1 Announce Type: cross Abstract: Meaning in Persian poetry is both historical and relational. Words persist through literary tradition while shifting their force through changing cons

Bi-Lipschitz Autoencoder With Injectivity Guarantee

arXiv:2604.06701v1 Announce Type: new Abstract: Autoencoders are widely used for dimensionality reduction, based on the assumption that high-dimensional data lies on low-dimensional manifolds. Regular

researcharxiv-cs-lg

Bias Redistribution in Visual Machine Unlearning: Does Forgetting One Group Harm Another?

arXiv:2604.08111v1 Announce Type: cross Abstract: Machine unlearning enables models to selectively forget training data, driven by privacy regulations such as GDPR and CCPA. However, its fairness impl

safetyarxiv-cs-cv

Contextual Earnings-22: A Speech Recognition Benchmark with Custom Vocabulary in the Wild

model-releasesarxiv-cs-cl

arXiv:2604.07354v1 Announce Type: new Abstract: The accuracy frontier of speech-to-text systems has plateaued on academic benchmarks.1 In contrast, industrial benchmarks and adoption in high-stakes do

ConvoLearn: A Dataset for Fine-Tuning Dialogic AI Tutors

arXiv:2601.08950v3 Announce Type: replace Abstract: Despite their growing adoption in education, LLMs remain misaligned with the core principle of effective tutoring: the dialogic construction of know

Dynamic Context Evolution for Scalable Synthetic Data Generation

arXiv:2604.07147v1 Announce Type: cross Abstract: Large language models produce repetitive output when prompted independently across many batches, a phenomenon we term cross-batch mode collapse: the p

Tutorials

Energy-based Tissue Manifolds for Longitudinal Multiparametric MRI Analysis

arXiv:2604.07180v1 Announce Type: cross Abstract: We propose a geometric framework for longitudinal multi-parametric MRI analysis based on patient-specific energy modelling in sequence space. Rather t

tutorialsarxiv-cs-ai

ETCH-X: Robustify Expressive Body Fitting to Clothed Humans with Composable Datasets

arXiv:2604.08548v1 Announce Type: new Abstract: Human body fitting, which aligns parametric body models such as SMPL to raw 3D point clouds of clothed humans, serves as a crucial first step for downst

Evaluating Low-Light Image Enhancement Across Multiple Intensity Levels

arXiv:2511.15496v2 Announce Type: replace Abstract: Imaging in low-light environments is challenging due to reduced scene radiance, which leads to elevated sensor noise and reduced color saturation. M

Fail2Drive: Benchmarking Closed-Loop Driving Generalization

arXiv:2604.08535v1 Announce Type: cross Abstract: Generalization under distribution shift remains a central bottleneck for closed-loop autonomous driving. Although simulators like CARLA enable safe an

Learning Without Losing Identity: Capability Evolution for Embodied Agents

arXiv:2604.07799v1 Announce Type: new Abstract: Embodied agents are expected to operate persistently in dynamic physical environments, continuously acquiring new capabilities over time. Existing appro

safetyarxiv-cs-ro

Physical Knot Classification Beyond Accuracy: A Benchmark and Diagnostic Study

arXiv:2603.23286v3 Announce Type: replace Abstract: Physical knot classification is a fine-grained task in which the intended cue is rope crossing structure, but high accuracy may still come from appe

Planning with Minimal Disruption

arXiv:2508.15358v2 Announce Type: replace Abstract: In many planning applications, we might be interested in finding plans that minimally modify the initial state to achieve the goals. We refer to thi

Quality-preserving Model for Electronics Production Quality Tests Reduction

arXiv:2604.06451v1 Announce Type: new Abstract: Manufacturing test flows in high-volume electronics production are typically fixed during product development and executed unchanged on every unit, even

safetyarxiv-cs-lg

Tarot-SAM3: Training-free SAM3 for Any Referring Expression Segmentation

arXiv:2604.07916v1 Announce Type: new Abstract: Referring Expression Segmentation (RES) aims to segment image regions described by natural-language expressions, serving as a bridge between vision and

Thompson Sampling for Infinite-Horizon Discounted Decision Processes

model-releasesarxiv-cs-lg

arXiv:2405.08253v3 Announce Type: replace-cross Abstract: This paper develops a viable notion of learning for sampling-based algorithms that applies in broader settings than previously considered. Mor

Training-free Spatially Grounded Geometric Shape Encoding (Technical Report)

arXiv:2604.07522v1 Announce Type: new Abstract: Positional encoding has become the de facto standard for grounding deep neural networks on discrete point-wise positions, and it has achieved remarkable

Visual prompting reimagined: The power of the Activation Prompts

model-releasesarxiv-cs-lg

arXiv:2604.06440v1 Announce Type: cross Abstract: Visual prompting (VP) has emerged as a popular method to repurpose pretrained vision models for adaptation to downstream tasks. Unlike conventional mo

What Drives Representation Steering? A Mechanistic Case Study on Steering Refusal

arXiv:2604.08524v1 Announce Type: cross Abstract: Applying steering vectors to large language models (LLMs) is an efficient and effective model alignment technique, but we lack an interpretable explan

safetyarxiv-cs-cl