Search: “models”

Low Rank Based Subspace Inference for the Laplace Approximation of Bayesian Neural Networks

model-releasesarxiv-cs-lg

arXiv:2502.02345v2 Announce Type: replace Abstract: Subspace inference for neural networks assumes that a subspace of their parameter space suffices to produce a reliable uncertainty quantification. I

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Memory-efficient Continual Learning with Prototypical Exemplar Condensation

DGX agent

arXiv:2603.13804v2 Announce Type: replace-cross Abstract: Rehearsal-based continual learning (CL) mitigates catastrophic forgetting by maintaining a subset of samples from previous tasks for replay. E

model-releasesarxiv-cs-ai

13 Apr 2026

Memory-Efficient Transfer Learning with Fading Side Networks via Masked Dual Path Distillation

arXiv:2604.09088v1 Announce Type: new Abstract: Memory-efficient transfer learning (METL) approaches have recently achieved promising performance in adapting pre-trained models to downstream tasks. Th

Neural networks for Text-to-Speech evaluation

arXiv:2604.08562v1 Announce Type: cross Abstract: Ensuring that Text-to-Speech (TTS) systems deliver human-perceived quality at scale is a central challenge for modern speech technologies. Human subje

Predicting Metabolic Dysfunction-Associated Steatotic Liver Disease using Machine Learning Methods: A Retrospective Cohort Study

arXiv:2510.22293v4 Announce Type: replace Abstract: Background: Metabolic dysfunction-associated steatotic liver disease (MASLD) affects 30-40% of US adults and is the most common chronic liver diseas

safetyarxiv-cs-lg

QuanBench+: A Unified Multi-Framework Benchmark for LLM-Based Quantum Code Generation

arXiv:2604.08570v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly used for code generation, yet quantum code generation is still evaluated mostly within single frameworks

SPASM: Stable Persona-driven Agent Simulation for Multi-turn Dialogue Generation

arXiv:2604.09212v1 Announce Type: new Abstract: Large language models are increasingly deployed in multi-turn settings such as tutoring, support, and counseling, where reliability depends on preservin

Structured Exploration and Exploitation of Label Functions for Automated Data Annotation

arXiv:2604.08578v1 Announce Type: cross Abstract: High-quality labeled data is critical for training reliable machine learning and deep learning models, yet manual annotation remains costly and error-

researcharxiv-cs-ai

Structured Uncertainty guided Clarification for LLM Agents

arXiv:2511.08798v2 Announce Type: replace-cross Abstract: LLM agents with tool-calling capabilities often fail when user instructions are ambiguous or incomplete, leading to incorrect invocations and

Local Ai

Temporal Patch Shuffle (TPS): Leveraging Patch-Level Shuffling to Boost Generalization and Robustness in Time Series Forecasting

arXiv:2604.09067v1 Announce Type: new Abstract: Data augmentation is a crucial technique for improving model generalization and robustness, particularly in deep learning models where training data is

local-aiarxiv-cs-lg

TRU: Targeted Reverse Update for Efficient Multimodal Recommendation Unlearning

arXiv:2604.02183v2 Announce Type: replace Abstract: Multimodal recommendation systems (MRS) jointly model user-item interaction graphs and rich item content, but this tight coupling makes user data di

ADAG: Automatically Describing Attribution Graphs

arXiv:2604.07615v1 Announce Type: new Abstract: In language model interpretability research, extbf{circuit tracing} aims to identify which internal features causally contributed to a particular outp

AgentOpt v0.1 Technical Report: Client-Side Optimization for LLM-Based Agent

arXiv:2604.06296v1 Announce Type: cross Abstract: AI agents are increasingly deployed in real-world applications, including systems such as Manus, OpenClaw, and coding agents. Existing research has pr

AVGen-Bench: A Task-Driven Benchmark for Multi-Granular Evaluation of Text-to-Audio-Video Generation

arXiv:2604.08540v1 Announce Type: cross Abstract: Text-to-Audio-Video (T2AV) generation is rapidly becoming a core interface for media creation, yet its evaluation remains fragmented. Existing benchma

Chunks as Arms: Multi-Armed Bandit-Guided Sampling for Long-Context LLM Preference Optimization

arXiv:2508.13993v2 Announce Type: replace Abstract: Long-context modeling is critical for a wide range of real-world tasks, including long-context question answering, summarization, and complex reason

ClawsBench: Evaluating Capability and Safety of LLM Productivity Agents in Simulated Workspaces

arXiv:2604.05172v2 Announce Type: replace Abstract: Large language model (LLM) agents are increasingly deployed to automate productivity tasks (e.g., email, scheduling, document management), but evalu

Tutorials

Cross-Modal Emotion Transfer for Emotion Editing in Talking Face Video

arXiv:2604.07786v1 Announce Type: new Abstract: Talking face generation has gained significant attention as a core application of generative models. To enhance the expressiveness and realism of synthe

tutorialsarxiv-cs-cv

Drift-Based Policy Optimization: Native One-Step Policy Learning for Online Robot Control

arXiv:2604.03540v2 Announce Type: replace Abstract: Although multi-step generative policies achieve strong performance in robotic manipulation by modeling multimodal action distributions, they require

safetyarxiv-cs-ro

DSCA: Dynamic Subspace Concept Alignment for Lifelong VLM Editing

arXiv:2604.07965v1 Announce Type: new Abstract: Model editing aims to update knowledge to add new concepts and change relevant information without retraining. Lifelong editing is a challenging task, p

EditCaption: Human-Aligned Instruction Synthesis for Image Editing via Supervised Fine-Tuning and Direct Preference Optimization

arXiv:2604.08213v1 Announce Type: new Abstract: High-quality training triplets (source-target image pairs with precise editing instructions) are a critical bottleneck for scaling instruction-guided im

Efficient and Effective Internal Memory Retrieval for LLM-Based Healthcare Prediction

arXiv:2604.07659v1 Announce Type: new Abstract: Large language models (LLMs) hold significant promise for healthcare, yet their reliability in high-stakes clinical settings is often compromised by hal

Efficient PRM Training Data Synthesis via Formal Verification

arXiv:2505.15960v3 Announce Type: replace Abstract: Process Reward Models (PRMs) have emerged as a promising approach for improving LLM reasoning capabilities by providing process supervision over rea

researcharxiv-cs-cl

Explainable AI to Improve Machine Learning Reliability for Industrial Cyber-Physical Systems

arXiv:2601.16074v2 Announce Type: replace Abstract: Industrial Cyber-Physical Systems (CPS) are sensitive infrastructure from both safety and economics perspectives, making their reliability criticall

safetyarxiv-cs-lg

FIT: A Large-Scale Dataset for Fit-Aware Virtual Try-On

arXiv:2604.08526v1 Announce Type: new Abstract: Given a person and a garment image, virtual try-on (VTO) aims to synthesize a realistic image of the person wearing the garment, while preserving their

Flemme: A Flexible and Modular Learning Platform for Medical Images

arXiv:2408.09369v3 Announce Type: replace-cross Abstract: As the rapid development of computer vision and the emergence of powerful network backbones and architectures, the application of deep learnin

Applications

GenLCA: 3D Diffusion for Full-Body Avatars from In-the-Wild Videos

arXiv:2604.07273v2 Announce Type: replace Abstract: We present GenLCA, a diffusion-based generative model for generating and editing photorealistic full-body avatars from text and image inputs. The ge

applicationsarxiv-cs-cv

Applications

HEX: Humanoid-Aligned Experts for Cross-Embodiment Whole-Body Manipulation

arXiv:2604.07993v1 Announce Type: new Abstract: Humans achieve complex manipulation through coordinated whole-body control, whereas most Vision-Language-Action (VLA) models treat robot body parts larg

applicationsarxiv-cs-ro

Holistic Optimal Label Selection for Robust Prompt Learning under Partial Labels

model-releasesarxiv-cs-lg

arXiv:2604.06614v1 Announce Type: cross Abstract: Prompt learning has gained significant attention as a parameter-efficient approach for adapting large pre-trained vision-language models to downstream

Lang2Act: Fine-Grained Visual Reasoning through Self-Emergent Linguistic Toolchains

arXiv:2602.13235v2 Announce Type: replace-cross Abstract: Visual Retrieval-Augmented Generation (VRAG) enhances Vision-Language Models (VLMs) by incorporating external visual documents to address a gi

Limits of Difficulty Scaling: Hard Samples Yield Diminishing Returns in GRPO-Tuned SLMs

arXiv:2604.06298v1 Announce Type: new Abstract: Recent alignment work on Large Language Models (LLMs) suggests preference optimization can improve reasoning by shifting probability mass toward better

safetyarxiv-cs-lg

LongSpec: Long-Context Lossless Speculative Decoding with Efficient Drafting and Verification

arXiv:2502.17421v4 Announce Type: replace-cross Abstract: As Large Language Models (LLMs) can now process extremely long contexts, efficient inference over these extended inputs has become increasingl

researcharxiv-cs-ai

LoRA-DA: Data-Aware Initialization for Low-Rank Adaptation via Asymptotic Analysis

arXiv:2510.24561v2 Announce Type: replace-cross Abstract: LoRA has become a widely adopted method for PEFT, and its initialization methods have attracted increasing attention. However, existing method

MedConclusion: A Benchmark for Biomedical Conclusion Generation from Structured Abstracts

arXiv:2604.06505v1 Announce Type: cross Abstract: Large language models (LLMs) are widely explored for reasoning-intensive research tasks, yet resources for testing whether they can infer scientific c

Novel View Synthesis as Video Completion

arXiv:2604.08500v1 Announce Type: new Abstract: We tackle the problem of sparse novel view synthesis (NVS) using video diffusion models; given K (approx 5) multi-view images of a scene and their

Open-Ended Instruction Realization with LLM-Enabled Multi-Planner Scheduling in Autonomous Vehicles

arXiv:2604.08031v1 Announce Type: cross Abstract: Most Human-Machine Interaction (HMI) research overlooks the maneuvering needs of passengers in autonomous driving (AD). Natural language offers an int

PASK: Toward Intent-Aware Proactive Agents with Long-Term Memory

arXiv:2604.08000v1 Announce Type: cross Abstract: Proactivity is a core expectation for AGI. Prior work remains largely confined to laboratory settings, leaving a clear gap in real-world proactive age

PhyEdit: Towards Real-World Object Manipulation via Physically-Grounded Image Editing

arXiv:2604.07230v2 Announce Type: replace Abstract: Achieving physically accurate object manipulation in image editing is essential for its potential applications in interactive world models. However,

Reasoning Fails Where Step Flow Breaks

arXiv:2604.06695v1 Announce Type: new Abstract: Large reasoning models (LRMs) that generate long chains of thought now perform well on multi-step math, science, and coding tasks. However, their behavi

researcharxiv-cs-ai

REVEAL: Reasoning-Enhanced Forensic Evidence Analysis for Explainable AI-Generated Image Detection

arXiv:2511.23158v2 Announce Type: replace-cross Abstract: The rapid progress of visual generative models has made AI-generated images increasingly difficult to distinguish from authentic ones, posing

RewardFlow: Generate Images by Optimizing What You Reward

arXiv:2604.08536v1 Announce Type: new Abstract: We introduce RewardFlow, an inversion-free framework that steers pretrained diffusion and flow-matching models at inference time through multi-reward La

safetyarxiv-cs-cv

SearchAD: Large-Scale Rare Image Retrieval Dataset for Autonomous Driving

arXiv:2604.08008v1 Announce Type: new Abstract: Retrieving rare and safety-critical driving scenarios from large-scale datasets is essential for building robust autonomous driving (AD) systems. As dat

SpecQuant: Spectral Decomposition and Adaptive Truncation for Ultra-Low-Bit LLMs Quantization

arXiv:2511.11663v2 Announce Type: replace-cross Abstract: The emergence of accurate open large language models (LLMs) has sparked a push for advanced quantization techniques to enable efficient deploy

SVGFusion: A VAE-Diffusion Transformer for Vector Graphic Generation

arXiv:2412.10437v3 Announce Type: replace Abstract: Generating high-quality Scalable Vector Graphics (SVGs) from text remains a significant challenge. Existing LLM-based models that generate SVG code

Visually-grounded Humanoid Agents

arXiv:2604.08509v1 Announce Type: new Abstract: Digital human generation has been studied for decades and supports a wide range of real-world applications. However, most existing systems are passively

When Personalization Tricks Detectors: The Feature-Inversion Trap in Machine-Generated Text Detection

arXiv:2510.12476v2 Announce Type: replace Abstract: Large language models (LLMs) have grown more powerful in language generation, producing fluent text and even imitating personal style. Yet, this abi

A Few Cases Are All You Need: An Empirical Study of Annotation-Efficient LoRA Fine-Tuning of MedSAM3

arXiv:2608.18731v1 Announce Type: cross Abstract: Medical image segmentation is essential for clinical workflows such as treatment planning and disease assessment. While specialist tools like TotalSeg

20 Aug 2026

Applications

Assessing Quality of Experience in Natural Language Generation of German Text

arXiv:2608.18888v1 Announce Type: new Abstract: The rapid advancement of Natural Language Generation (NLG) has made the reliable evaluation of generated text increasingly critical, as these systems, s

applicationsarxiv-cs-cl

20 Aug 2026

BERTilda: Explainable Topic Lifecycle Tracking with Split/Merge Detection via Similarity-and-Flow Temporal Graphs