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Research
Research, evidence gathering, literature, reports, investigation, and synthesis
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Showing 12,025–12,048 of 21,385 skills
- Dolq Ode Discovery LlmDoLQ: Discovering Ordinary Differential Equations with LLM-based qualitative and quantitative evaluation. Multi-agent architecture for symbolic regression of governing ODEs from data. Sampler Agent proposes candidates, Parameter Optimizer refines equations, Scientist Agent uses LLM for combined qualitative (domain knowledge) and quantitative (fit metrics) evaluation to iteratively guide search. Accepted at ICML 2026. Use when: ODE discovery, symbolic regression, scientific ML, equation discov...Votes: 0GitHub stars: 3
- Distillation Game DefenseProduct-of-Experts (PoE) defense against adaptive distillation attacks — a minimax game framework between a utility-constrained teacher and an adaptive student that reweights high-value examples. PoE is a simple forward-pass-only defense combining teacher with proxy student during generation (arXiv: 2605.22737).Votes: 0GitHub stars: 3
- Discrete Signaling Chaotic Regularization RnnDiscrete signaling mediates chaotic regularization in recurrent neural networks - linking microscopic chaos to macroscopic neural representation geometryVotes: 0GitHub stars: 3
- Discounted Mpc Plant Model MismatchDiscounted MPC under plant-model mismatch - stability and suboptimality analysis for infinite-horizon optimal control with surrogate models. Activation: MPC, model predictive control, plant-model mismatch, robustness, stability, discounted control.Votes: 0GitHub stars: 3
- Dimensionality Modularity Continual LearningFramework for understanding when architectural modularity matters in continual learning based on representational dimensionality. Shows that modular networks only outperform monolithic ones in low-dimensional regimes where representational geometry is constrained. Triggers: continual learning dimensionality, modular vs monolithic networks, representational geometry, stability-plasticity tradeoff, structure matters continual learning.Votes: 0GitHub stars: 3
- Cortical Microcircuits Information Flux OptimizationSimulation-based reverse engineering study of cortical microcircuit information flux. Analyzes whether cortical microcircuits are optimized for information flux in recurrent networks. Use when: studying cortical circuit optimization, information theory in neural networks, reverse engineering brain circuits, analyzing mutual information between network states, comparing biological vs artificial neural circuit architectures.Votes: 0GitHub stars: 3
- Cortical Microcircuit Information Flux OptimizationSimulation-based reverse engineering methodology for analyzing how cortical microcircuits optimize information flux (mutual information between successive network states). Use when: (1) studying information-theoretic properties of recurrent neural circuits, (2) analyzing the role of embedding networks in cortical microcolumns, (3) investigating recurrence resonance and entropy-driven dynamics, (4) designing reservoir computing systems with optimal information processing.Votes: 0GitHub stars: 3
- Computational Lesions Multilingual Language Models SeparateCausal framework for studying multilingual brain-model alignment using targeted "computational lesions" in multilingual LLMs. Zero out parameters to separate shared vs language-specific brain processing. Use when: multilingual LLM analysis, brain-model alignment, fMRI encoding studies, computational lesions, cross-lingual neuroscience, language processing in brain. Trigger: computational lesion, multilingual brain alignment, language-specific processing, fMRI encoding models, shared backbone,...Votes: 0GitHub stars: 3
- Computational Auditory Periphery ModelsCross-species computational modeling of the auditory periphery using 1-D nonlinear cochlear transmission-line models adapted across human, mouse, and gerbil. Covers species-specific anatomical/physiological parameterization, BM mechanics, OHC deficits, and cochlear synaptopathy simulation.Votes: 0GitHub stars: 3
- Coding Agents Social Science ResearchCoding agents in social sciences research methodology — using AI coding agents to automate data analysis, simulation, and empirical research in economics, political science, and sociology. Covers reproducibility, agent reliability, and domain-specific challenges.Votes: 0GitHub stars: 3
- Chaotic Regularization Recurrent NetworksLink microscopic chaos in recurrent neural networks to macroscopic geometry of neural representations using kernel methods and dynamical mean-field theory. Chaotic dynamics act as intrinsic regularizer enhancing generalization while preserving expressivity.Votes: 0GitHub stars: 3
- Chaos Synchrony Ei NetworksExtended Sompolinsky-Crisanti-Sommers (SCS) theory for two-population Excitatory-Inhibitory networks with target-specific inhibition. DMFT derivation of phase diagrams showing quiescence, asynchronous chaos, persistent activity, structured chaos, and coherent oscillations. Shows target-specific inhibition determines which collective instability dominates. Activation: SCS E/I theory, DMFT neural networks, chaos-synchrony transition, E/I balance, neural phase diagram, 兴奋抑制网络混沌.Votes: 0GitHub stars: 3
- Byte Modeling Efficiency GapCompute-matched scaling analysis of byte-level modeling revealing context fragility disparity between MDM and AR paradigms, with structural bias recommendations for modality-agnostic designs.Votes: 0GitHub stars: 3
- Balanced Network Scaling ConductanceEmpirical scaling laws in balanced networks with conductance-based synapses. Shows that conductance-based synapses + spike time correlations together produce realistic membrane potential variability — neither alone suffices. Activation: balanced network scaling, conductance synapse, membrane variability, spike time correlation, current-based synapse.Votes: 0GitHub stars: 3
- Attractor Fcm Gradient DescentGradient descent-based physics-constrained Jacobian Fuzzy Cognitive Map (FCM) with attractor dynamics, residual memory, and BPTT. Uses Newton's method for fixed point attractor finding with adaptive landscape manipulation. Triggers: attractor FCM, fuzzy cognitive map gradient, FCM attractor dynamics, physics-constrained FCM, Jacobian FCM.Votes: 0GitHub stars: 3
- Attention Residuals注意力残差（AttnRes）方法论。改进 Transformer 注意力机制的残差连接。 提升模型性能和训练稳定性。 触发词：注意力残差、AttnRes、注意力机制、残差连接、Transformer优化、 attention residuals, attention mechanism, residual connection。Votes: 0GitHub stars: 3
- Ai Multi Agent ResearchMethodology for coordinating multiple AI agents in autonomous research workflows. Covers parallel agent orchestration with diverse initialization, shared communication forums, independent experimentation with shared knowledge, cross-domain generalization testing, reward hacking detection, and the taste-vs-volume tradeoff. Use when: designing multi-agent research systems, orchestrating parallel AI experimentation, building autonomous discovery pipelines, or evaluating automated research qualit...Votes: 0GitHub stars: 3
- Ai Math DiscoveryAI-assisted mathematical discovery methodology. Use when: (1) collaborating with LLMs to generate mathematical conjectures, inequalities, bounds, or proofs; (2) verifying AI-generated mathematical results; (3) structuring human-AI mathematical research workflows; (4) exploring AI's role in mathematical research; (5) analyzing mathematical inequality patterns (Gaussian perimeter, moment comparison, autoconvolution, Sidon sets, Szarek's inequality). Trigger words: AI math discovery, Grokability...Votes: 0GitHub stars: 3
- Ai Interpretability Dead SalmonStatistical-causal reframing of AI interpretability: treating explanations as parameters of statistical models inferred from computational traces, with uncertainty quantification and testing against alternative computational hypotheses. Inspired by the famous 'dead salmon fMRI' study. Activation: dead salmon AI, interpretability statistics, causal interpretability, explanation uncertainty, statistical AI explanation, false discovery interpretability.Votes: 0GitHub stars: 3
- Ai Enabled Cyber Threats Mitre AttackMethodology from Anthropic research (Jun 3, 2026) mapping a year's worth of AI-enabled cyber threats using MITRE ATT&CK framework — threat categorization, attack pattern analysis, and security implications.Votes: 0GitHub stars: 3
- Ai Enabled Cyber Threat MappingMethodology for mapping real-world AI-enabled cyber attacks onto MITRE ATT&CK framework with AI Risk Enablement Score (ARiES) — identifying patterns in how threat actors weaponize AI for cyber operations.Votes: 0GitHub stars: 3
- Serp Self Evolutionary ReplanningSERP - Self-Evolutionary RePlanningVotes: 0GitHub stars: 3
- Se Search Self Evolving SearchSE-Search - Self-Evolving Search AgentVotes: 0GitHub stars: 3
- Live Evo Online Evolution AgenticLive-Evo - Online Evolution of Agentic MemoryVotes: 0GitHub stars: 3