Research

Research, evidence gathering, literature, reports, investigation, and synthesis

skills in category: 21,409
pages available: 893

Security grades appear on each card once the skill has been scanned. Newly imported skills may briefly show without a grade until the backfill job runs.

Open in full browser

Browse research skills

Showing 11,425–11,448 of 21,409 skills

Arxiv 2608 19964 G Mark Grounded Multi Agent Reasoning For CooperatAG-MARK: Grounded Multi-Agent Reasoning for Cooperative Driving via Knowledge Graphs (arXiv: 2608.19964)researchgogitVotes: 0GitHub stars: 3
Arxiv 2608 19950 Designing Human Mediated Ai Guidance Ready TogetheADesigning Human-mediated AI Guidance: Ready Together for Personalized Family Emergency Preparedness (arXiv: 2608.19950)researchgoVotes: 0GitHub stars: 3
Arxiv 2608 19932 A Strong Linear Baseline For Whole Heart Cardiac SAA Strong Linear Baseline for Whole-Heart Cardiac Shape Completion on CT, with an Open Eleven-Structure Statistical Shape Model (arXiv: 2608.19932)researchgoVotes: 0GitHub stars: 3
Arxiv 2608 19903 Where Does The Union Bound Go Best Arm IdentificatAWhere Does the Union Bound Go? Best-Arm Identification and Strong FWER Control (arXiv: 2608.19903)researchgotestingVotes: 0GitHub stars: 3
Arxiv 2608 19901 Maliciousskillbench A Comprehensive Benchmark ForAMaliciousSkillBench: A Comprehensive Benchmark for Malicious Agent Skill Detection (arXiv: 2608.19901)researchgoVotes: 0GitHub stars: 3
Arxiv 2608 19891 Eximo Vlm Guided Exploration Of Vla PoliciesAEXIMO: VLM Guided Exploration of VLA Policies (arXiv: 2608.19891)researchgoperformanceVotes: 0GitHub stars: 3
Arxiv 2608 19047v1 Eureka Task Conditioned Meta Agent Orchestration FA**arXiv ID:** 2608.19047v1 **Authors:** Alizer Wong, Heng Cui, Yi Tan, Xiongchao Zhan, Liang Lin, Yuxiang Guo, Zhaorong Dai, Zixin Zeng, Wenyuan Li **URL:** http://arxiv.org/abs/2608.19047v1 **Utility Score:** 1.00researchVotes: 0GitHub stars: 3
Arxiv 2608 04738 Evigraph Evidence Guided Autonomous Research AgentAEviGraph: Evidence-Guided Autonomous Research Agents (arXiv: 2608.04738)researchVotes: 0GitHub stars: 3
Arex Towards A Recursively Self Improving Agent ForAAREX: Towards a Recursively Self-Improving Agent for Deep ResearchresearchgoVotes: 0GitHub stars: 3
Approximating Gradients For Differentiable Quality Diversity In Reinforcement LearningA**arXiv ID:** 2202.03666 **Authors:** Bryon Tjanaka, Matthew C. Fontaine, Julian Togelius, Stefanos Nikolaidis **Published:** 2022-02-08T05:53:55Z **Abstract:** Consider the problem of training robustly capable agents. One approach is to generate a diverse collection of agent polices. Training can then be viewed as a quality diversity (QD) optimization problem, where we search for a collection of performant policies that are diverse with respect to quantified behavior. Recent work shows that ...researchgogitVotes: 0GitHub stars: 3
Approximately Optimal Search On A Higherdimensional Sliding PuzzleA**arXiv ID:** 2412.01937 **Authors:** Nono SC Merleau, Miguel O'Malley, Érika Roldán, Sayan Mukherjee **Published:** 2024-12-02T19:59:06Z **Abstract:** Higher-dimensional sliding puzzles are constructed on the vertices of a $d$-dimensional hypercube, where $2^d-l$ vertices are distinctly coloured. Rings with the same colours are initially set randomly on the vertices of the hypercube. The goal of the puzzle is to move each of the $2^d-l$ rings to pre-defined target vertices on the cube. In th...researchgoVotes: 0GitHub stars: 3
Agenticgeo A Selfevolving Agentic System For Generative Engine OptimizationA**arXiv ID:** 2603.20213 **Authors:** Jiaqi Yuan, Jialu Wang, Zihan Wang, Qingyun Sun, Ruijie Wang, Jianxin Li **Published:** 2026-03-02T16:13:13Z **Abstract:** Generative search engines represent a transition from traditional ranking-based retrieval to Large Language Model (LLM)-based synthesis, transforming optimization goals from ranking prominence towards content inclusion. Generative Engine Optimization (GEO), specifically, aims to maximize visibility and attribution in black-box summari...researchgogitVotes: 0GitHub stars: 3
Agent Reliability Come Cross Benchmark Decomposition Verification Loops SpeciASkill derived from arXiv:2607.17044 - Where Does Agent Reliability Come From? A Cross-Benchmark Decomposition of Verification Loops, SpeciresearchVotes: 0GitHub stars: 3
Aflow Agentic Workflow GenerationASkill for AI agent capabilitiesresearchpythonnodeVotes: 0GitHub stars: 3
A Reinforcement Learning Based Encoderdecoder Framework For Learning Stock Trading RulesA**arXiv ID:** 2101.03867 **Authors:** Mehran Taghian, Ahmad Asadi, Reza Safabakhsh **Published:** 2021-01-08T13:19:01Z **Abstract:** A wide variety of deep reinforcement learning (DRL) models have recently been proposed to learn profitable investment strategies. The rules learned by these models outperform the previous strategies specially in high frequency trading environments. However, it is shown that the quality of the extracted features from a long-term sequence of raw prices of the inst...researchperformanceVotes: 0GitHub stars: 3
A Diagnostic Framework For Ai Agent BehaviorADerived from arXiv:2607.17149 - A Diagnostic Framework for AI Agent BehaviorresearchgoexpressVotes: 0GitHub stars: 3
Mtc Conductance Spiking NetworksAMulti-Timescale Conductance Spiking Networks (MTC-SNN) — gradient-trainable spiking neural networks where neural dynamics emerge from shaping the I-V curve via fast, slow, and ultra-slow conductances. Enables tonic, phasic, and bursting firing regimes within a single model, trainable via exact BPTT without surrogate gradients. arXiv: 2605.11835 (May 2026).researchpythongitVotes: 0GitHub stars: 3
Moving Mri Brain ImagingAMoving MRI (mMRI) methodology for imaging during large-scale motion. Core idea: Move subject and scanner (magnet, gradients, RF coil) as a single unit to minimize relative motion, enabling neuroimaging during movement. Demonstrates cryogen-free superconducting magnet on pneumatically actuated tilt platform. Enables vestibular function studies during natural head motion. Activation: moving MRI, mMRI, motion MRI, vestibular imaging, motion artifact MRI, naturalistic neuroimaging, superconductin...researchgogitVotes: 0GitHub stars: 3
Module Lattice SecurityAModule lattice security methodology for post-quantum cryptography. Covers unconditional verification of Weber's conjecture, Principal Ideal Problem solvability, Structured CVP Distance on the Log-Unit Lattice, Ring-LWE and Module-LWE security reductions, and cyclotomic field arithmetic. Combines computational number theory (Fukuda-Komatsu sieve, Herbrand's theorem, Coarse Lattice Theorem, Trigamma Theorem) with lattice-based cryptographic security analysis. Activation: module lattice security...researchpythongoVotes: 0GitHub stars: 3
Modular State Space Model 260714078AModel human perception, cognition, and decision dynamics as a modular perception-cognition-decision pipeline state-space model. Provides mathematical formulation, stability conditions, and application to rehabilitation control. Use when you need interpretable dynamical models linking neural mechanisms to behavior.researchgoexpressVotes: 0GitHub stars: 3
Modular Memristor Synaptic PlasticityA模块化忆阻器模型：具有突触样可塑性和易失性记忆特性。通过可重构的忆阻器阵列实现类突触动力学，支持在线学习和自适应权重更新。适用于神经形态硬件、边缘学习设备、存内计算。researchpythongoVotes: 0GitHub stars: 3
Modal Neural Modality DiscoveryAMoDAl (Modality Decorrelation and Alignment) framework for self-supervised neural modality discovery in speech neuroprosthesis. Uses contrastive alignment with LLM text embeddings + decorrelation loss to discover complementary neurolinguistic modalities from multiple brain regions. Key innovation: proves contrastive alignment induces transitive modality coalescence, which decorrelation must counteract. Trigger words: MoDAl, neural modality discovery, speech neuroprosthesis, brain-to-text deco...researchpythongoVotes: 0GitHub stars: 3
Mllm Brain Alignment Task ProbingATask-conditioned probing methodology for evaluating brain alignment of instruction-tuned multimodal LLMs (MLLMs) using fMRI. Activation: brain-MLLM alignment, instruction-tuned MLLM, task-conditioned probing, brain encoding, fMRI-MLLM, voxel-wise encodingresearchpythongoVotes: 0GitHub stars: 3
Ml Qec Threshold OptimizationAMachine learning methodology for finding optimal quantum error correction (QEC) thresholds. Combines ML search strategies with quantum error correction analysis to determine noise thresholds where QEC codes break down.researchgoperformanceVotes: 0GitHub stars: 3