Search: “framework”

Matryoshka Language Model Suites

arXiv:2608.09703v1 Announce Type: new Abstract: Training a language model suite classically requires training each model separately and serving them independently. We improve both training and inferen

MCIF: Multimodal Crosslingual Instruction-Following Benchmark from Scientific Talks

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DGX agent

arXiv:2507.19634v4 Announce Type: replace-cross Abstract: Recent advances in large language models have laid the foundation for multimodal LLMs (MLLMs), which unify text, speech, and vision within a s

model-releasesarxiv-cs-ai

11 Aug 2026

MDB-Link: Hierarchical Schema Linking for Multi-Database Text-to-SQL

arXiv:2608.09588v1 Announce Type: new Abstract: Traditional Text-to-SQL research and benchmarks assume a known target database, overlooking settings in which a query must be routed within a large, het

researcharxiv-cs-cl

MetaSpace: Metamorphic Testing for Spatial Cognition in Embodied Agents

arXiv:2608.07533v1 Announce Type: new Abstract: An embodied agent is an intelligent entity that interacts with its environment through a physical body. Currently, the evaluation of embodied agents pri

ML-Based Hierarchical Prediction for Practical Energy Scheduling in Dynamic NTN-WPT Systems

arXiv:2608.08804v1 Announce Type: cross Abstract: With advancements in long-distance wireless power transfer (WPT) and space-based energy technologies, integrating WPT into non-terrestrial networks (N

safetyarxiv-cs-lg

MoE-Prism: Disentangling Monolithic Experts for Elastic MoE Services via Model-System Co-Designs

arXiv:2510.19366v2 Announce Type: replace Abstract: Mixture-of-Experts (MoE) scales model capacity through sparse activation, and is becoming an important architecture for large language models (LLMs)

researcharxiv-cs-cl

Applications

Motion-Aware Animatable Gaussian Avatars Deblurring

arXiv:2411.16758v4 Announce Type: replace Abstract: The creation of 3D human avatars from multi-view videos is a significant yet challenging task in computer vision. However, existing techniques rely

applicationsarxiv-cs-cv

MotionCraft: Latent World Modeling with Sparse Attention for Visual Upscaling

arXiv:2608.08553v1 Announce Type: new Abstract: Video super-resolution (VSR) aims to recover high-fidelity high-resolution videos from low-resolution inputs and is central to applications ranging from

safetyarxiv-cs-cv

MRI super-resolution in ten sampling steps using a diffusion bridge model

arXiv:2608.08819v1 Announce Type: new Abstract: Objective. MRI provides excellent soft-tissue contrast, but long acquisition times can cause patient discomfort and lead to motion artifacts, forcing a

Multi-Branch Policy Optimization for Multimodal Large Language Models

arXiv:2608.07581v1 Announce Type: cross Abstract: Group-based reinforcement learning methods for multimodal large language models typically rely on trajectory-level credit assignment that applies a si

Tutorials

Multi-Granular Node Pruning for Causal Circuit Discovery

arXiv:2512.10903v3 Announce Type: replace Abstract: Circuit discovery aims to identify minimal subnetworks that are responsible for specific behaviors in large language models (LLMs). Existing approac

tutorialsarxiv-cs-ai

Multi-Submap Implicit Neural SLAM with Local-to-Global Loop Closure for Large-Scale Scene Reconstruction

arXiv:2608.09146v1 Announce Type: new Abstract: Neural Radiance Fields (NeRF)-based SLAM has demonstrated impressive results in small-scale scene reconstruction, yet scaling these methods to extensive

local-aiarxiv-cs-cv

Multilingual Agent-Based World Modeling for Social Science

arXiv:2512.07195v2 Announce Type: replace-cross Abstract: Multi-agent role-playing has recently shown promise for studying social behavior with language agents, but existing simulations are mostly mon

Multimodal Federated Learning under Dual-Axis Modality Missingness

arXiv:2608.09240v1 Announce Type: cross Abstract: Multimodal federated learning (FL) supports collaborative modeling in privacy-sensitive health-sensing and medical settings, but realistic deployments

local-aiarxiv-cs-ai

Multimodal Model Diffing for Feature Discovery and Control

arXiv:2608.09928v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) exhibit strong visual understanding, yet the internal features that cause these behaviors remain difficult to

Multimodal Skin Lesion Classification with Swin Transformer and Clinical Metadata Fusion

arXiv:2608.07574v1 Announce Type: new Abstract: Skin lesion classification plays an important role in supporting the early diagnosis of skin cancer. However, automated analysis remains challenging due

MusicLayout: Explicit Structural Planning for Controllable Text-to-Music Generation

arXiv:2608.09035v1 Announce Type: cross Abstract: Text-to-music generation has advanced rapidly, but current systems still rely primarily on global text prompts, leaving the structural organization of

NeuPAT: Neuron-aware Plasticity Allocation Tuning for Language-Preserving MLLMs

arXiv:2608.08107v1 Announce Type: cross Abstract: Multimodal expansion of large language models (LLMs) enables new perceptual capabilities but often compromises the language intelligence acquired duri

neuralGAM: An R Package for Fitting Generalized Additive Neural Networks

arXiv:2505.08610v2 Announce Type: replace-cross Abstract: Nowadays, Neural Networks are considered one of the most effective methods for various tasks such as anomaly detection, computer-aided disease

researcharxiv-cs-lg

NewtonGS: Physics-Structured Object-Level Neural Newtonian Dynamics for Gaussian Scene Animation

arXiv:2608.07598v1 Announce Type: new Abstract: Animating objects in a static 3D Gaussian scene requires an explicit object-level dynamic state and a controllable model of object motion. Existing dyna

Not All Frames Deserve Full Computation: Accelerating Autoregressive Video Generation via Selective Computation and Predictive Extrapolation

arXiv:2604.02979v2 Announce Type: replace Abstract: Autoregressive (AR) video diffusion models enable long-form video generation but remain expensive due to repeated multi-step denoising. Existing tra

OATS: Online Data Augmentation for Time Series Foundation Models

arXiv:2601.19040v2 Announce Type: replace Abstract: Time Series Foundation Models (TSFMs) are a powerful paradigm for time series analysis and are often enhanced by synthetic data augmentation to impr

researcharxiv-cs-lg

OGG-FR: Orthogonal Gradient Gaming and Frequency Rectification for Unmanned Aerial Vehicle Infrared Image Super-Resolution

model-releasesarxiv-cs-cv

arXiv:2608.09150v1 Announce Type: new Abstract: Unmanned aerial vehicle (UAV) infrared image super-resolution aims to recover weak thermal structures for deployment on resource-constrained platforms;

Omni2LoRA: Coherence-Preserving Parametric Memory for Efficient Omni Language Models

arXiv:2608.09227v1 Announce Type: new Abstract: Omnimodal language models (OLMs) enable unified audio-visual understanding, but processing long joint token sequences makes inference computationally pr

On the use of foundation models in cognitive science

arXiv:2608.07812v1 Announce Type: new Abstract: A host of recent studies have evaluated the cognitive and developmental alignment of Foundation Models (FMs). These investigations include evaluations o

safetyarxiv-cs-cl

One Adapter Pair per Model: A Universal Activation Interface for Language Models

arXiv:2608.09521v1 Announce Type: new Abstract: Activation-based tools are usually tied to one model's native hidden space, requiring probes, sparse autoencoders, and natural-language interpreters to

One-Time Training for All Grains: Open-Set Grain Recognition and Quantitative Analysis

arXiv:2608.09345v1 Announce Type: new Abstract: Advances in crop breeding have introduced an increasing number of grain varieties, creating a growing demand for efficient variety recognition and quant

local-aiarxiv-cs-cv

Optimal Multi-Agent Path Finding in Continuous Time

model-releasesarxiv-cs-ro

arXiv:2508.16410v3 Announce Type: replace-cross Abstract: Continuous-time Conflict Based Search (CCBS) has been widely used as an exact baseline for Continuous-time Multi-Agent Path Finding (MAPFR), a

Out-of-Distribution Federated Distillation with Domain-Aware Proxy

model-releasesarxiv-cs-lg

arXiv:2608.08525v1 Announce Type: new Abstract: Federated Learning is a distributed machine learning paradigm that trains a global model by aggregating local clients without sharing private data of ea

P2Voxel: Pyramid Pivot Voxelization for 3D Mesh Tokenization

arXiv:2608.07549v1 Announce Type: cross Abstract: Triangle meshes provide explicit and accurate surface geometry, yet their irregular topology connectivity makes 3D mesh tokenization a geometric sampl

local-aiarxiv-cs-ai

PAM: Training Policy-Aligned Moderation Filters at Scale

arXiv:2505.19766v4 Announce Type: replace Abstract: Large language models (LLMs) remain vulnerable to misalignment and jailbreaks, making external safeguards like moderation filters essential, yet exi

safetyarxiv-cs-cl

PARAGraph: Pathology-Anatomy-Aware Hierarchical Graph for Diabetic Retinopathy Grading

arXiv:2608.08368v1 Announce Type: new Abstract: Diabetic retinopathy (DR) remains a leading cause of vision loss among working-age adults worldwide, making reliable severity grading clinically importa

PE-Mamba: Bidirectional Selective Layer Aggregation for AI-Generated Image Detection

arXiv:2608.07999v1 Announce Type: new Abstract: AI-generated image (AIGI) detection has become increasingly challenging due to the rapid advancement of generative models and the diminishing gap betwee

Perception Before Supervision: Self-Contained Visual Distillation from Counterfactual Blind Spots

arXiv:2608.09931v1 Announce Type: new Abstract: Self-improvement for multimodal large language models (MLLMs) is typically driven by reward-based methods that provide only coarse scalar feedback. Dist

safetyarxiv-cs-cv

Personalized Federated Learning via Variance-Aware Nonparametric Empirical Bayes

model-releasesarxiv-cs-lg

arXiv:2608.09074v1 Announce Type: cross Abstract: We develop a new approach to Personalized Federated Learning across heterogeneous clients using Nonparametric Empirical Bayes (NPEB). Leveraging the a

Personalized Lower-limb Exoskeleton Assistance via Preference-based Bayesian Optimization

model-releasesarxiv-cs-ro

arXiv:2608.09015v1 Announce Type: new Abstract: A significant challenge in exoskeleton robotics is the need to dynamically adapt control profiles to individual motion preferences, thereby ensuring bot

Persuasive and Compliant Tendencies Predict Group Decision-Making in Humans and Language Models

arXiv:2608.08199v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly involved in group decision-making with other LLMs and humans. Yet it remains unclear whether their influen

PhysAttNet: Enhancing Predictive Performance in Industrial and Astrophysical Time Series via Physics-Informed Attention

arXiv:2608.07681v1 Announce Type: new Abstract: Accurate and robust time series forecasting is essential in many applications involving physical processes, such as manufacturing monitoring and astroph

safetyarxiv-cs-lg

PIVOT: Preference-based Intervention Vectors for Pedagogical Tutor Steering

arXiv:2608.07509v1 Announce Type: cross Abstract: LLMs are increasingly used for conversational tutoring, but effective tutoring requires more than correct answers. Tutors must choose when to scaffold

PluginEval: A Diagnostic Benchmark for Fine-Grained Error Attribution in Function Calling

arXiv:2608.08700v1 Announce Type: new Abstract: Reliable evaluation of tool routing is critical as Large Language Models increasingly operate as autonomous agents. Current benchmarks face three struct

PolypSteer: Counterfactual Endoscopic Synthesis via Training-Free Activation Steering

arXiv:2603.07066v2 Announce Type: replace-cross Abstract: Generative diffusion models are increasingly used for medical imaging data augmentation, but text prompting cannot produce causal training dat

Population-Level Generative Modeling for Ranking Data

model-releasesarxiv-cs-lg

arXiv:2608.08422v1 Announce Type: cross Abstract: Ranking data arise in scientific and machine learning applications, including recommendation systems, information retrieval, voting, marketing, and AI

Agents

Population-Scalable Multi-Agent World Modeling

arXiv:2608.08600v1 Announce Type: cross Abstract: World models have recently achieved impressive progress in visual prediction and interactive generation, but extending them to multi-agent environment

agentsarxiv-cs-ai

Predict to Skip: Linear Multistep Feature Forecasting for Efficient Diffusion Transformers

arXiv:2602.18093v2 Announce Type: replace Abstract: Diffusion Transformers (DiT) have emerged as a widely adopted backbone for high-fidelity image and video generation, yet their iterative denoising p

Applications

PreGress: Ranking-Native Pre-training and Prompting for Graph Node Ranking

arXiv:2608.09016v1 Announce Type: cross Abstract: Node ranking is a fundamental problem in graph information retrieval, measuring the relative importance of nodes and supporting a wide range of applic

applicationsarxiv-cs-lg

PressureMesh: 3D Human Mesh Estimation from Multi-Device Pressure Images

arXiv:2608.09550v1 Announce Type: new Abstract: Human pose monitoring is crucial in fields such as rehabilitation assessment and human-computer interaction. Due to its privacy-preserving nature, press

PRISM: A Predictive Protocol for Permutation Optimization via Landscape Diagnostics

arXiv:2608.08344v1 Announce Type: cross Abstract: Permutation optimization arises whenever the components of a system are fixed but their ordering affects performance. We introduce PRISM, a predictive

PRISM-Delta: Differential Subspace Steering for Prompt Highlighting in Large Language Models

arXiv:2603.10705v2 Announce Type: replace Abstract: Prompt highlighting steers a large language model to prioritize user-specified text spans during generation. A key challenge of existing Key-editing

researcharxiv-cs-cl