Search: “framework”

LiFT: Does Instruction Fine-Tuning Improve In-Context Learning for Longitudinal Modelling by Large Language Models?

arXiv:2604.16382v1 Announce Type: new Abstract: Longitudinal NLP tasks require reasoning over temporally ordered text to detect persistence and change in human behavior and opinions. However, in-conte

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Light-Adapted Electroretinogram and Oscillatory Potentials (LEOPs) Dataset for Autism Spectrum Disorder and Typically Developing Individuals

DGX agent

arXiv:2604.16981v1 Announce Type: cross Abstract: The LEOPs (Light-ERG-Oscillatory Potentials) dataset provides light-adapted (LA) electroretinogram (ERG) and Oscillatory Potentials (OPs) waveforms fo

researcharxiv-cs-lg

21 Apr 2026

Live Avatar: Streaming Real-time Audio-Driven Avatar Generation with Infinite Length

arXiv:2512.04677v5 Announce Type: replace Abstract: Audio-driven avatar interaction demands real-time, streaming, and infinite-length generation -- capabilities fundamentally at odds with the sequenti

LIVE: Leveraging Image Manipulation Priors for Instruction-based Video Editing

arXiv:2604.17021v1 Announce Type: new Abstract: Video editing aims to modify input videos according to user intent. Recently, end-to-end training methods have garnered widespread attention, constructi

LiveFact: A Dynamic, Time-Aware Benchmark for LLM-Driven Fake News Detection

arXiv:2604.04815v2 Announce Type: replace Abstract: The rapid development of Large Language Models (LLMs) has transformed fake news detection and fact-checking tasks from simple classification to comp

Agents

LLM as a Tool, Not an Agent: Code-Mined Tree Transformations for Neural Architecture Search

arXiv:2604.16555v1 Announce Type: cross Abstract: Neural Architecture Search (NAS) aims to automatically discover high-performing deep neural network (DNN) architectures. However, conventional algorit

agentsarxiv-cs-cv

Local Inconsistency Resolution: The Interplay between Attention and Control in Probabilistic Models

arXiv:2604.17140v1 Announce Type: cross Abstract: We present a generic algorithm for learning and approximate inference with an intuitive epistemic interpretation: iteratively focus on a subset of the

Local learning for stable backpropagation-free neural network training towards physical learning

arXiv:2603.24790v2 Announce Type: replace Abstract: While backpropagation and automatic differentiation have driven deep learning's success, the physical limits of chip manufacturing and rising enviro

applicationsarxiv-cs-lg

LOGICAL-COMMONSENSEQA: A Benchmark for Logical Commonsense Reasoning

arXiv:2601.16504v3 Announce Type: replace Abstract: Commonsense reasoning often involves evaluating multiple plausible interpretations rather than selecting a single atomic answer, yet most benchmarks

LoRA on the Go: Instance-level Dynamic LoRA Selection and Merging

arXiv:2511.07129v3 Announce Type: replace Abstract: Low-Rank Adaptation (LoRA) has emerged as a parameter-efficient approach for fine-tuning large language models. However, conventional LoRA adapters

Lower Bounds and Proximally Anchored SGD for Non-Convex Minimization Under Unbounded Variance

arXiv:2604.16620v1 Announce Type: new Abstract: Analysis of Stochastic Gradient Descent (SGD) and its variants typically relies on the assumption of uniformly bounded variance, a condition that freque

LTRR: Learning To Rank Retrievers for LLMs

arXiv:2506.13743v2 Announce Type: replace Abstract: Retrieval-Augmented Generation (RAG) systems typically rely on a single fixed retriever, despite growing evidence that no single retriever performs

researcharxiv-cs-cl

MambaKick: Early Penalty Direction Prediction from HAR Embeddings

arXiv:2604.16588v1 Announce Type: new Abstract: Penalty kicks in soccer are decided under extreme time constraints, where goalkeepers benefit from anticipating shot direction from the kickers motion b

applicationsarxiv-cs-cv

Mammo-FM: Breast-specific foundational model for Integrated Mammographic Diagnosis, Prognosis, and Reporting

arXiv:2512.00198v2 Announce Type: replace Abstract: Breast cancer is one of the leading causes of death among women worldwide. We introduce Mammo-FM, the first foundation model specifically for mammog

safetyarxiv-cs-cv

MASPO: Unifying Gradient Utilization, Probability Mass, and Signal Reliability for Robust and Sample-Efficient LLM Reasoning

arXiv:2602.17550v3 Announce Type: replace Abstract: Existing Reinforcement Learning with Verifiable Rewards (RLVR) algorithms, such as GRPO, rely on rigid, uniform, and symmetric trust region mechanis

safetyarxiv-cs-lg

MathFlow: Enhancing the Perceptual Flow of MLLMs for Visual Mathematical Problems

arXiv:2503.16549v2 Announce Type: replace Abstract: Despite strong results on many tasks, multimodal large language models (MLLMs) still underperform on visual mathematical problem solving, especially

Maximizing Local Entropy Where It Matters: Prefix-Aware Localized LLM Unlearning

arXiv:2601.03190v3 Announce Type: replace Abstract: Machine unlearning aims to forget sensitive knowledge from Large Language Models (LLMs) while maintaining general utility. However, existing approac

MeasHalu: Mitigation of Scientific Measurement Hallucinations for Large Language Models with Enhanced Reasoning

arXiv:2604.16929v1 Announce Type: new Abstract: The accurate extraction of scientific measurements from literature is a critical yet challenging task in AI4Science, enabling large-scale analysis and i

Measuring Distribution Shift in User Prompts and Its Effects on LLM Performance

arXiv:2604.17650v1 Announce Type: new Abstract: LLMs are increasingly deployed in dynamic, real-world settings, where the distribution of user prompts can shift substantially over time as new tasks, p

applicationsarxiv-cs-cl

Measuring Representation Robustness in Large Language Models for Geometry

arXiv:2604.16421v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly evaluated on mathematical reasoning, yet their robustness to equivalent problem representations remains po

Medical Image Understanding Improves Survival Prediction via Visual Instruction Tuning

arXiv:2604.18250v1 Announce Type: new Abstract: Accurate prognostication and risk estimation are essential for guiding clinical decision-making and optimizing patient management. While radiologist-ass

MEDN: Motion-Emotion Feature Decoupling Network for Micro-Expression Recognition

arXiv:2604.17899v1 Announce Type: new Abstract: Unlike macro-expression, micro-expression does not follow a strictly consistent mapping rule between emotions and Action Units (AUs). As a result, some

MedPRMBench: A Fine-grained Benchmark for Process Reward Models in Medical Reasoning

arXiv:2604.17282v1 Announce Type: new Abstract: Process-Level Reward Models (PRMs) are essential for guiding complex reasoning in large language models, yet existing PRM benchmarks cover only general

MedProbeBench: Systematic Benchmarking at Deep Evidence Integration for Expert-level Medical Guideline

arXiv:2604.18418v1 Announce Type: new Abstract: Recent advances in deep research systems enable large language models to retrieve, synthesize, and reason over large-scale external knowledge. In medici

Memorize When Needed: Decoupled Memory Control for Spatially Consistent Long-Horizon Video Generation

arXiv:2604.18215v1 Announce Type: new Abstract: Spatially consistent long-horizon video generation aims to maintain temporal and spatial consistency along predefined camera trajectories. Existing meth

tutorialsarxiv-cs-cv

Agents

Memory Centric Power Allocation for Multi-Agent Embodied Question Answering

arXiv:2604.17810v1 Announce Type: new Abstract: This paper considers multi-agent embodied question answering (MA-EQA), which aims to query robot teams on what they have seen over a long horizon. In co

agentsarxiv-cs-ro

mEOL: Training-Free Instruction-Guided Multimodal Embedder for Vector Graphics and Image Retrieval

arXiv:2604.17054v1 Announce Type: new Abstract: Scalable Vector Graphics (SVGs) function both as visual images and as structured code that encode rich geometric and layout information, yet most method

MetaLint: Easy-to-Hard Generalization for Code Linting

arXiv:2507.11687v4 Announce Type: replace-cross Abstract: Large language models excel at code generation but struggle with code linting, particularly in generalizing to unseen or evolving best practic

MetaMem: Evolving Meta-Memory for Knowledge Utilization through Self-Reflective Symbolic Optimization

arXiv:2602.11182v2 Announce Type: replace Abstract: Existing memory systems enable Large Language Models (LLMs) to support long-horizon human-LLM interactions by persisting historical interactions bey

tutorialsarxiv-cs-cl

Mind the Way You Select Negative Texts: Pursuing the Distance Consistency in OOD Detection with VLMs

arXiv:2603.02618v3 Announce Type: replace Abstract: Out-of-distribution (OOD) detection seeks to identify samples from unknown classes, a critical capability for deploying machine learning models in o

Missing Pattern Tree based Decision Grouping and Ensemble for Enhancing Pair Utilization in Deep Incomplete Multi-View Clustering

arXiv:2512.21510v2 Announce Type: replace-cross Abstract: Real-world multi-view data often exhibit highly inconsistent missing patterns, posing significant challenges for incomplete multi-view cluster

MM-Hand: A 21-DOF Multi-modal Modular Dexterous Robotic Hand with Remote Actuation

arXiv:2604.17245v1 Announce Type: new Abstract: High-DOF dexterous hands require compact actuation, rich sensing, and reliable thermal behavior, but conventional designs often occupy valuable in-hand

tutorialsarxiv-cs-ro

Modeling Biomechanical Constraint Violations for Language-Agnostic Lip-Sync Deepfake Detection

arXiv:2604.16808v1 Announce Type: new Abstract: Current lip-sync deepfake detectors rely on pixel-level artifacts or audio-visual correspondence, failing to generalize across languages because these c

researcharxiv-cs-cv

MoE-nD: Per-Layer Mixture-of-Experts Routing for Multi-Axis KV Cache Compression

arXiv:2604.17695v1 Announce Type: cross Abstract: KV cache memory is the dominant bottleneck for long-context LLM inference. Existing compression methods each act on a single axis of the four-dimensio

researcharxiv-cs-cl

More Than Sum of Its Parts: Deciphering Intent Shifts in Multimodal Hate Speech Detection

arXiv:2603.21298v2 Announce Type: replace Abstract: Combating hate speech on social media is critical for securing cyberspace, yet relies heavily on the efficacy of automated detection systems. As con

Agents

MoRI: Learning Motivation-Grounded Reasoning for Scientific Ideation in Large Language Models

arXiv:2603.19044v2 Announce Type: replace Abstract: Scientific ideation aims to propose novel solutions within a given scientific context. Existing LLM-based agentic approaches emulate human research

agentsarxiv-cs-cl

MTSQL-R1: Towards Long-Horizon Multi-Turn Text-to-SQL via Agentic Training

arXiv:2510.12831v3 Announce Type: replace Abstract: Multi-turn Text-to-SQL aims to translate a user's conversational utterances into executable SQL while preserving dialogue coherence and grounding to

MU-GeNeRF: Multi-view Uncertainty-guided Generalizable Neural Radiance Fields for Distractor-aware Scene

arXiv:2604.17965v1 Announce Type: new Abstract: Generalizable Neural Radiance Fields (GeNeRFs) enable high-quality scene reconstruction from sparse views and can generalize to unseen scenes. However,

applicationsarxiv-cs-cv

Multi-Beholder: Biomarker Prediction for Low-Grade Glioma with Multiple Instance Learning and One-Class Classification

arXiv:2310.07464v2 Announce Type: replace-cross Abstract: Biomarker detection is an indispensable part of the diagnosis and treatment of low-grade glioma (LGG). However, current LGG biomarker detectio

Multilevel neural networks with dual-stage feature fusion for human activity recognition

arXiv:2604.16577v1 Announce Type: new Abstract: Human activity recognition (HAR) refers to the process of identifying human actions and activities using data collected from sensors. Neural networks, s

Multimodal Policy Internalization for Conversational Agents

arXiv:2510.09474v2 Announce Type: replace Abstract: Modern conversational agents like ChatGPT and Alexa+ rely on predefined policies specifying metadata, response styles, and tool-usage rules. As thes

safetyarxiv-cs-cl

MuSteerNet: Human Reaction Generation from Videos via Observation-Reaction Mutual Steering

arXiv:2603.20187v2 Announce Type: replace Abstract: Video-driven human reaction generation aims to synthesize 3D human motions that directly react to observed video sequences, which is crucial for bui

researcharxiv-cs-cv

Navigating the Conceptual Multiverse

arXiv:2604.17815v1 Announce Type: cross Abstract: When language models answer open-ended problems, they implicitly make hidden decisions that shape their outputs, leaving users with uncontextualized a

safetyarxiv-cs-cl

Neural Network-Based Adaptive Event-Triggered Control for Dual-Arm Unmanned Aerial Manipulator Systems

arXiv:2604.17048v1 Announce Type: new Abstract: This paper investigates the control problem of dual-arm unmanned aerial manipulator systems (DAUAMs). Strong coupling between the dual-arm and the multi

researcharxiv-cs-ro

Neuro-Symbolic Resolution of Recommendation Conflicts in Multimorbidity Clinical Guidelines

arXiv:2604.17340v1 Announce Type: new Abstract: Clinical guidelines, typically developed by independent specialty societies, inherently exhibit substantial fragmentation, redundancy, and logical contr

NI Sampling: Accelerating Discrete Diffusion Sampling by Token Order Optimization

arXiv:2604.18471v1 Announce Type: new Abstract: Discrete diffusion language models (dLLMs) have recently emerged as a promising alternative to traditional autoregressive approaches, offering the flexi

NIM4-ASR: Towards Efficient, Robust, and Customizable Real-Time LLM-Based ASR

arXiv:2604.18105v1 Announce Type: cross Abstract: Integrating large language models (LLMs) into automatic speech recognition (ASR) has become a mainstream paradigm in recent years. Although existing L

Noise Injection: Improving Out-of-Distribution Generalization for Limited Size Datasets

arXiv:2511.03855v2 Announce Type: replace Abstract: Deep learned (DL) models for image recognition have been shown to fail to generalize to data from different devices, populations, etc. COVID-19 dete

tutorialsarxiv-cs-cv