All categories
Tools & Automation
CLI tools, utilities, converters, workflow automation, and productivity helpers
- 49,293
- 2,054
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 browserBrowse tools & automation skills
Showing 18,793–18,816 of 49,293 skills
- Serverlesst2i Efficient Text To Image Workflow SerServerlessT2I: Efficient Text-to-Image Workflow Serving on a Serverless PlatformVotes: 0GitHub stars: 3
- Search Fail Recover A Training Framework For Correction Aware ReasoningMany reasoning tasks are not well described by a single left-to-right chain: a solver may need to pursue a plausible branch, observe delayed failure, and return to the latest prefix that can still be. Based on arXiv:2607.07492.Votes: 0GitHub stars: 3
- Rl Post Training Builds Compositional Reasoning StrategiesDoes RL post-training merely amplify primitive skills already latent in a base model, or can it compose primitive skills into new higher-level strategies? We study this question in a fully observable. Based on arXiv:2607.07646.Votes: 0GitHub stars: 3
- Quasirecurrent Neural Networks**arXiv ID:** 1611.01576 **Authors:** James Bradbury, Stephen Merity, Caiming Xiong, Richard Socher **Published:** 2016-11-05T00:31:25Z **Abstract:** Recurrent neural networks are a powerful tool for modeling sequential data, but the dependence of each timestep's computation on the previous timestep's output limits parallelism and makes RNNs unwieldy for very long sequences. We introduce quasi-recurrent neural networks (QRNNs), an approach to neural sequence modeling that alternates convoluti...Votes: 0GitHub stars: 3
- Physics Infused Video GenerationPhysics-Infused Video Generation via joint modeling of visual and latent physical dynamics. Phantom integrates physical-aware video representation into generation process for physically consistent video synthesis. Use for: physics-aware video generation, physical dynamics modeling, consistent video synthesis, latent physics inference. Activation: Phantom, physics-infused video, physical dynamics, video generation, latent physics, 物理注入视频生成.Votes: 0GitHub stars: 3
- Perceptioninformed Neural Networks Beyond Physicsinformed Neural Networks**arXiv ID:** 2505.03806 **Authors:** Mehran Mazandarani, Marzieh Najariyan **Published:** 2025-05-02T09:08:07Z **Abstract:** This article introduces Perception-Informed Neural Networks (PrINNs), a framework designed to incorporate perception-based information into neural networks, addressing both systems with known and unknown physics laws or differential equations. Moreover, PrINNs extend the concept of Physics-Informed Neural Networks (PINNs) and their variants, offering a platform for the...Votes: 0GitHub stars: 3
- Paper Llm EvalSkill for AI agent capabilitiesVotes: 0GitHub stars: 3
- Pals Percentile Aware Layerwise Sparsity For Llm PruningOne-shot pruning methods like Wanda and SparseGPT apply the same sparsity ratio to every layer of a transformer, ignoring known variation in layer importance. We propose PALS (Percentile-Aware Layerwi. Based on arXiv:2607.07557.Votes: 0GitHub stars: 3
- Optimizeanything A Universal Api For Optimizing Any Text Parameter**arXiv ID:** 2605.19633 **Authors:** Lakshya A Agrawal, Donghyun Lee, Shangyin Tan, Wenjie Ma, Karim Elmaaroufi, Rohit Sandadi, Sanjit A. Seshia, Koushik Sen, Dan Klein, Ion Stoica, Joseph E. Gonzalez, Omar Khattab, Alexandros G. Dimakis, Matei Zaharia **Published:** 2026-05-19T10:18:12Z **Abstract:** Can a single LLM-based optimization system match specialized tools across fundamentally different domains? We show that when optimization problems are formulated as improving a text artifact ev...Votes: 0GitHub stars: 3
- On The Biological Plausibility Of Orthogonal Initialisation For Solving Gradient Instability In Deep Neural Networks**arXiv ID:** 2211.08408 **Authors:** Nikolay Manchev, Michael Spratling **Published:** 2022-10-27T06:08:06Z **Abstract:** Initialising the synaptic weights of artificial neural networks (ANNs) with orthogonal matrices is known to alleviate vanishing and exploding gradient problems. A major objection against such initialisation schemes is that they are deemed biologically implausible as they mandate factorization techniques that are difficult to attribute to a neurobiological process. This pa...Votes: 0GitHub stars: 3
- Mxnorm Reusing Mxfp Block Scales For Efficient Tensor Normalisation**arXiv ID:** 2603.13180 **Authors:** Callum McLean, Luke Y. Prince, Alexandre Payot, Paul Balança, Carlo Luschi **Published:** 2026-03-13T17:14:06Z **Abstract:** Matrix multiplication performance has long been the major bottleneck to scaling deep learning workloads, which has stimulated the design of new accelerators that use increasingly low-precision number formats. However, improvements in matrix multiplication performance have far outstripped improvements in performance on reductions and...Votes: 0GitHub stars: 3
- Max Out Grpo Signal Adaptive Trace Prefix Control For Hard Reasoning ProblemsGroup Relative Policy Optimization (GRPO) stalls on a models hardest problems: when no rollout in a group succeeds, the group-relative advantages vanish and the problem contributes no gradient, wasti. Based on arXiv:2607.07674.Votes: 0GitHub stars: 3
- Learning Evolution Via Optimization Knowledge Adaptation**arXiv ID:** 2501.02200 **Authors:** Chao Wang, Lingling Li, Licheng Jiao, Jiaxuan Zhao, Fang Liu, Shuyuan Yang **Published:** 2025-01-04T05:35:21Z **Abstract:** The iterative search process of evolutionary algorithms (EAs) encapsulates optimization knowledge within historical populations and fitness evaluations. Effective utilization of this knowledge is crucial for facilitating knowledge transfer and online adaptation. However, current research typically addresses these goals in isolation ...Votes: 0GitHub stars: 3
- Large Language Model As Metasurrogate For Datadriven Manytask Optimization A Proofofprinciple Study**arXiv ID:** 2503.08301 **Authors:** Xian-Rong Zhang, Yue-Jiao Gong, Yuan-Ting Zhong, Ting Huang, Jun Zhang **Published:** 2025-03-11T11:13:11Z **Abstract:** In many-task optimization scenarios, surrogate models are valuable for mitigating the computational burden of repeated fitness evaluations across tasks. This study proposes a novel meta-surrogate framework to assist many-task optimization, by leveraging the knowledge transfer strengths and emergent capabilities of large language models ...Votes: 0GitHub stars: 3
- Gift Geometry Informed Low Precision Gradient Communication For Llm PretrainingGradient communication is a primary scaling bottleneck in large language model (LLM) pretraining. Communicating gradients in low-precision formats, such as FP8 and NVFP4, can significantly reduce the. Based on arXiv:2607.07494.Votes: 0GitHub stars: 3
- Fas R1 A Unified Multi Task Mllm For Reasoning FacFAS-R1: A Unified Multi-Task MLLM for Reasoning Face Anti-SpoofingVotes: 0GitHub stars: 3
- Discovering Heuristics With Large Language Models Llms For Mixedinteger Programs Singlemachine Scheduling**arXiv ID:** 2510.24013 **Authors:** İbrahim Oğuz Çetinkaya, İ. Esra Büyüktahtakın, Parshin Shojaee, Chandan K. Reddy **Published:** 2025-10-28T02:43:04Z **Abstract:** Our study contributes to the scheduling and combinatorial optimization literature with new heuristics discovered by leveraging the power of Large Language Models (LLMs). We focus on the single-machine total tardiness (SMTT) problem, which aims to minimize total tardiness by sequencing n jobs on a single processor without preem...Votes: 0GitHub stars: 3
- Dels Spec Decoupled Long Short Contexts For Parallel Speculative DraftingSpeculative decoding accelerates LLM inference by drafting multiple tokens and verifying them in parallel. Block-parallel drafters such as DFlash further improve drafting efficiency by predicting an e. Based on arXiv:2607.07409.Votes: 0GitHub stars: 3
- Classic Continual And Contrastive Learning Of Aspect Sentiment Classification Tasks**arXiv ID:** 2112.02714 **Authors:** Zixuan Ke, Bing Liu, Hu Xu, Lei Shu **Published:** 2021-12-05T23:55:53Z **Abstract:** This paper studies continual learning (CL) of a sequence of aspect sentiment classification(ASC) tasks in a particular CL setting called domain incremental learning (DIL). Each task is from a different domain or product. The DIL setting is particularly suited to ASC because in testing the system needs not know the task/domain to which the test data belongs. To our knowle...Votes: 0GitHub stars: 3
- Arxiv 2609 10305v1 Rilm Parameter Efficient Language Modeling Via Geo**arXiv ID:** 2609.10305v1 **Authors:** Fang Li **URL:** http://arxiv.org/abs/2609.10305v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2609 10264v1 Maverick Private And Verifiable Llm Inference Made**arXiv ID:** 2609.10264v1 **Authors:** Ben Merbaum, Mohammad Amin Raeisi, Wenhao Wang, Charalampos Papamanthou, Katerina Sotiraki, Fan Zhang **URL:** http://arxiv.org/abs/2609.10264v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2609 10239v1 Literag Cost Efficient Graph Based Retrieval Augme**arXiv ID:** 2609.10239v1 **Authors:** Daniel Alejandro Coll Tejeda, Pedro García López, Daniel Barcelona-Pons **URL:** http://arxiv.org/abs/2609.10239v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2609 10135v1 Agent Based Ml Llm Fusion With Self Optimizing Pro**arXiv ID:** 2609.10135v1 **Authors:** Shuai Yan, Yang Xu, Shan He **URL:** http://arxiv.org/abs/2609.10135v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3
- Arxiv 2609 10060v1 Reference Based Bias Detection In Llms Via Relativ**arXiv ID:** 2609.10060v1 **Authors:** Marek Jeliński, Jan Dubiński, Maciej Chrabaszcz, Sebastian Cygert **URL:** http://arxiv.org/abs/2609.10060v1 **Utility Score:** 1.00Votes: 0GitHub stars: 3