Search: “framework”

GPA-RAM: Grasp-Pretraining Augmented Robotic Attention Mamba for Spatial Task Learning

arXiv:2504.19683v4 Announce Type: replace Abstract: Fine-grained robotic manipulation often fails when inaccurate initial grasps propagate errors and necessitate complex pose correction. We propose Gr

researcharxiv-cs-ro

Human

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GQ-FSL: Green Quantized Federated Split Learning

DGX agent

arXiv:2607.29659v1 Announce Type: new Abstract: Deploying state-of-the-art deep neural networks (DNNs) at the wireless edge is severely bottlenecked by the strict energy and resource constraints of mo

local-aiarxiv-cs-lg

3 Aug 2026

Harnessing the Wisdom of LLM Crowds through Complementarity-Driven Iterative Collaboration

arXiv:2607.29087v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed in enterprise settings, yet individual models remain bounded by model-specific capability limitat

HierDoc: Hierarchical Page-to-Region Evidence Routing for Long-Document Visual Question Answering

arXiv:2607.29638v1 Announce Type: new Abstract: Multi-page document visual question answering requires locating sparse evidence at both the page and region levels. Existing approaches typically emphas

How Hard Does It Think? Analyzing Step-Aware Reasoning Energy in LLM Chain-of-Thought Trajectories

arXiv:2607.28674v1 Announce Type: new Abstract: Understanding how computational effort is allocated across individual chain-of-thought (CoT) reasoning steps remains an open challenge: existing interpr

Incorporating data drift to perform survival analysis on credit risk

arXiv:2601.20533v2 Announce Type: replace-cross Abstract: Survival analysis has become a standard approach for modelling time to default by time-varying covariates in credit risk. Unlike most existing

safetyarxiv-cs-lg

InferQ: A Database-Oriented Benchmark for Quantum Circuits Simulation

arXiv:2607.29134v1 Announce Type: cross Abstract: Recent work suggests that relational database management systems (RDBMSs) can execute quantum circuit simulation by compiling the simulation into SQL

Is It Time for the Renaissance of Salient Object Detection in the Era of MLLMs?

arXiv:2607.29222v1 Announce Type: new Abstract: The zero-shot capabilities of multimodal large language models (MLLMs) are pushing salient object detection (SOD) beyond task-specific supervision. To d

Knowledge Restoration-driven Prompt Optimization: Unlocking LLM Potential for Open-Domain Relational Triplet Extraction

arXiv:2601.15037v2 Announce Type: replace-cross Abstract: Open-domain Relational Triplet Extraction (ORTE) aims to mine structured knowledge without predefined relation schemas. Large Language Models

researcharxiv-cs-ai

Latent Lie-Poisson Neural Networks (LLPNNs): Discovering the motion of Lie-Poisson systems through observable data and latent dynamics

arXiv:2607.28939v1 Announce Type: new Abstract: Structure-preserving neural networks are essential for the long-term prediction of Hamiltonian systems from data. Many important Hamiltonian systems in

Latent Sculpting for Zero-Shot Generalization: A Manifold Learning Approach to Out-of-Distribution Anomaly Detection

arXiv:2512.22179v3 Announce Type: replace Abstract: Detecting previously unseen attacks remains a major challenge for machine learning-based intrusion detection systems. Deep models trained on network

Learning Latent Reasoning Traces for Scalar Reward Models End-to-End

arXiv:2607.29185v1 Announce Type: new Abstract: Reward models (RMs) are central to aligning large language models with human preferences via reinforcement learning. Although traditional scalar RMs ena

safetyarxiv-cs-cl

Learning Optimal Dynamic Matching via Graph Neural Networks

arXiv:2607.28925v1 Announce Type: new Abstract: Dynamic matching markets require decisions about whom to match and when: matching now yields value but removes participants who may create better future

Learning to Predict Performance-induced Emotion Differences in Classical Piano Music

arXiv:2607.28876v1 Announce Type: cross Abstract: Music is often used as a medium for communicating emotion, with performers shaping perceived affect through interpretation. This study addresses the c

LegoQ: Density-Matrix Representation Learning with Spectral-Spatial State Transitions for Hyperspectral Classification

arXiv:2607.28970v1 Announce Type: new Abstract: Hyperspectral image classification is complicated by mixed pixels, spectral ambiguity, class imbalance, and limited annotations. Most current classifier

researcharxiv-cs-cv

LEMUR: Learning to Align with Multi-Objective Reinforcement Learning from Preference Feedback

arXiv:2607.29559v1 Announce Type: new Abstract: Reinforcement Learning (RL) systems are typically trained using a single, well-specified scalar reward function. However, real-world decision-making tas

Applications

Leveraging Image Generators to Address Data Scarcity: The Gen4Regen Dataset for Forest Regeneration Mapping

arXiv:2605.05627v2 Announce Type: replace-cross Abstract: Sustainable forest management relies on precise species composition mapping, yet traditional ground surveys are labour-intensive and geographi

applicationsarxiv-cs-ai

Agents

MerchantBench: Benchmarking LLM Agents for Long-Term Coherence in E-Commerce Operations

arXiv:2607.28956v1 Announce Type: new Abstract: Large language model agents are increasingly evaluated as autonomous tool users, yet most benchmarks focus on bounded tasks with immediate success crite

agentsarxiv-cs-ai

Meshy T2: Fast Native Mesh Generation with Flow Matching

arXiv:2607.28675v1 Announce Type: cross Abstract: Polygonal meshes are the standard surface representation of modern 3D pipelines, and generating high-quality meshes with artist-style topology is esse

researcharxiv-cs-cv

Agents

Mixture-of-Translators: Translating KV Caches Across Heterogeneous Large Language Models

arXiv:2607.28979v1 Announce Type: new Abstract: Heterogeneous Large Language Model (LLM) systems increasingly rely on shared contexts, retrieved evidence, and multi-agent dialogue histories, yet their

agentsarxiv-cs-cl

MMFGU: Multimodal Federated Graph Unlearning

arXiv:2607.28708v1 Announce Type: new Abstract: Multimodal federated graph learning enables clients to collaboratively train graph models over structural, textual, and visual signals without sharing p

local-aiarxiv-cs-lg

MoRoute: Dynamic Routing for In-Context Multimodal Video Generation

arXiv:2607.29545v1 Announce Type: new Abstract: Multimodal video generation aims to generate and edit videos conditioned on arbitrary combinations of text, images, and videos within a single model, al

MOT-SR: Multi-Objective Tool-Augmented Scientific Equation Discovery with Large Language Models

arXiv:2607.29561v1 Announce Type: cross Abstract: Symbolic Regression (SR) aims to discover analytical equations from observational data and plays a central role in scientific modeling. While recent L

local-aiarxiv-cs-ai

MROPE: A Multi-Robot Safe Cooperative Strategy via combined Predictive Safety Filters and Ellipse-based Constraint Compression

arXiv:2607.29203v1 Announce Type: new Abstract: Deploying drone swarms to track a dynamic target in cluttered environments presents severe computational and safety challenges. We propose MROPE, a hier

safetyarxiv-cs-ro

Multi-Agent Planning with Spatio-Temporal and Topological Constraints using STL-GO

arXiv:2607.28679v1 Announce Type: new Abstract: Multi-agent planning problems arise in a variety of engineering applications, such as multi-robot wildfire fighting and unmanned aerial inspection in fa

Multi-Modal Object Re-Identification with Dual Semantic Guidance and Global-Local Mutual Modulation

arXiv:2607.29207v1 Announce Type: new Abstract: Multi-modal object Re-Identification (ReID) aims to retrieve target instances by leveraging complementary information across modalities. However, existi

Multi-Source Multi-View Graph Domain Adaptation with Hyperbolic Residual Encoding for Cross-Site MDD Identification from rs-fMRI

arXiv:2607.29531v1 Announce Type: new Abstract: Cross-site identification of major depressive disorder (MDD) from resting-state functional magnetic resonance imaging (rs-fMRI) is hindered by inter-sit

Nice benchmark to measure agentic e-commerce capabilities. They ran an agent for one simulated year of e-commerce operations and it ends up …

Nice benchmark to measure agentic e-commerce capabilities. They ran an agent for one simulated year of e-commerce operations and it ends up with 27.3% of the money a human makes. MerchantBench is a 36

model-releasesdair-ai--x

Nonparametric Partial Disentanglement via Mechanism Sparsity: Sparse Actions, Interventions and Sparse Temporal Dependencies

arXiv:2401.04890v2 Announce Type: replace-cross Abstract: This work introduces a novel principle for disentanglement we call mechanism sparsity regularization, which applies when the latent factors of

On the Generalization of Steering Vectors for Chain-of-Thought Faithfulness

arXiv:2607.29062v1 Announce Type: new Abstract: Model capabilities have improved in large part due to scaling chain of thought. This has been a promising development for AI safety--where models verbal

Open-Source LLM-Driven Formal Verification: A Multi-Agent Pipeline for RTL Repair

arXiv:2607.28877v1 Announce Type: cross Abstract: Verification consumes the majority of modern chip design effort, yet the formal verification tools that provide mathematical guarantees of correctness

OPERA: Online Data Pruning for Efficient Retrieval Model Adaptation

arXiv:2603.17205v3 Announce Type: replace-cross Abstract: Domain-specific finetuning is essential for dense retrievers, yet not all data pairs contribute equally to the learning process. We introduce

researcharxiv-cs-ai

Optimal Resource Allocation for ML Model Training and Deployment under Concept Drift

arXiv:2512.12816v2 Announce Type: replace Abstract: We study how to allocate resources for training and deployment of machine learning (ML) models under concept drift and limited budgets. We consider

local-aiarxiv-cs-lg

Parameter-Efficient Fine-Tuning for Spiking Point Cloud Models

arXiv:2607.29048v1 Announce Type: new Abstract: Spiking Neural Networks (SNNs) offer energy-efficient solutions for point cloud analysis on resource-constrained devices through event-driven computatio

Paris: A Decentralized Trained Open-Weight Diffusion Model

arXiv:2510.03434v3 Announce Type: replace-cross Abstract: We present Paris, the first publicly released diffusion model pre-trained entirely through decentralized computation. Paris demonstrates that

Physics-Embedded Neural ODEs for Learning Antagonistic Pneumatic Artificial Muscle Dynamics

arXiv:2602.23670v2 Announce Type: replace Abstract: Pneumatic artificial muscles (PAMs) enable compliant actuation for soft wearable, assistive, and interactive robots. When arranged antagonistically,

researcharxiv-cs-ro

PhyUnfold-Net: Advancing Remote Sensing Change Detection with Physics-Guided Deep Unfolding

arXiv:2603.19566v3 Announce Type: replace Abstract: Bi-temporal change detection is highly sensitive to acquisition discrepancies, including illumination, season, and atmosphere, which often cause fal

researcharxiv-cs-cv

RAPiD: Reward-Guided Consistency Distillation of Diffusion Planners for Real-Time Autonomous Driving

arXiv:2602.07339v2 Announce Type: replace Abstract: Diffusion-based trajectory planners can model multi-modal driving behavior, but their iterative denoising process introduces a latency bottleneck fo

Reasoning in Real World Clinical Care: Why Large Language Models Are Not Yet Safe for Autonomous Clinical Decision Support

arXiv:2607.28677v1 Announce Type: new Abstract: LLM now pass medical licensing examinations and, in curated cases, can rival physicians at diagnostic reasoning. These developments have accelerated the

Reflection or Re-Generation? Why LLM Revision Fails Where Human Revision Succeeds

arXiv:2607.28908v1 Announce Type: new Abstract: Reflection, the ability to revisit and revise prior reasoning, is central to how humans improve their answers. Large language models (LLMs) are increasi

local-aiarxiv-cs-lg

Representations from Pretrained Machine-Learning Interatomic Potentials as Coarse Coordinates for Material Generation and Evaluation

arXiv:2607.28776v1 Announce Type: new Abstract: Generative machine learning is increasingly used for inorganic crystal structure generation. Most models and the corresponding evaluation approaches rel

ReSum: Synergizing LLM Reasoning and Summarization with Reinforcement Learning

arXiv:2606.13316v2 Announce Type: replace Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) is a central technique for improving long-horizon reasoning in Large Language Models (LLMs). H

researcharxiv-cs-ai

RynnBrain 1.1: Towards More Capable and Generalizable Embodied Foundation Model

model-releasesarxiv-cs-ro

arXiv:2607.17977v2 Announce Type: replace Abstract: We present RynnBrain 1.1, a family of embodied foundation models spanning 2B, 9B, and 122B-A10B scales. Trained with a unified spatio-temporal and p

SAF-OPD: Stable Advantage Fusion for On-Policy Distillation

arXiv:2607.29209v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards (RLVR) broadcasts a single response-level reward to every token, while on-policy distillation (OPD) sco

SafeNexus: Discovering and Steering Modality-Universal Safety Neurons in MLLMs

arXiv:2607.28969v1 Announce Type: new Abstract: Although Large Language Models (LLMs) have demonstrated promising safety performance, extending them to Multimodal Large Language Models (MLLMs) exposes

local-aiarxiv-cs-cv

SAGP: Semantic Affordance-Guided Grasp Planning via Coarse-Zone VLM Reasoning

arXiv:2607.29374v1 Announce Type: new Abstract: Geometry-based grasp planners ensure physically valid grasps but ignore functional semantics, often generating grasps that are antipodal and collision-f

safetyarxiv-cs-ro

SAM+D: Parameter-Efficient Dimensional Lifting of SAM-Family Models via Depth-Routed LoRA and Depth Shifting

arXiv:2607.29033v1 Announce Type: new Abstract: Existing methods for adapting 2D foundation models such as SAM to 3D volumes either process slices independently---ignoring inter-slice context---or req

SatEdit: Mask-Conditioned Image Editing via VLM-Guided Segment Annotation

arXiv:2607.29367v1 Announce Type: new Abstract: Satellite image editing requires spatially precise object-level control, but supervised editing datasets for overhead imagery are costly to build becaus