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klavis. Klavis AI: MCP integration platforms that let AI agents use tools reliably at any scale

MUA-RL. MUA-RL: MULTI-TURN USER-INTERACTING AGENT REINFORCEMENT LEARNING FOR AGENTIC TOOL USE

Toucan. Official repo of Toucan: Synthesizing 1.5M Tool-Agentic Data from Real-World MCP Environments

ProbSurgery. Pytorch implementation for ICML 2025 Paper “Representation Surgery in Model Merging with Probabilistic Modeling”

Minimal-GRPO. Fine-tuning Open Language Models (like LlaMa, Qwen) for Tasks with verifiable rewards using Group Relative Policy Optimization (GRPO) or Evolutionary Strategy (ES)

Awesome-Long2short-on-LRMs. Awesome-Long2short-on-LRMs is a collection of state-of-the-art, novel, exciting long2short methods on large reasoning models. It contains papers, codes, datasets, evaluations, and analyses.

Long-to-Short-via-Model-Merging. Model merging is a highly efficient approach for long-to-short reasoning.

Awesome-Unified-Multimodal. 📖 This is a repository for organizing papers, codes, and other resources related to unified multimodal models.

Foundations-of-LLMs. A book for Learning the Foundations of LLMs

fintech-literature. Fintech literature, including journal, conference, book and useful links

ClimaX. Foundation model for weather & climate

CPL-ICML2024. [ICML'24 Oral] Offical code repo for ICML2024 paper "Candidate Pseudolabel Learning: Enhancing Vision-Language Models by Prompt Tuning with Unlabeled Data"

SDM. Converting Artificial Neural Networks to Ultra-Low-Latency Spiking Neural Networks for Action Recognition

VLMs-Adversarial-Robustness.

ITEM. Pytorch implementation of the paper "Debiased Sample Selection for Combating Noisy Labels"

BadLabels. Challenging label noise called BadLabel; Robust label-noise learning called Robust DivideMix

Self-Filtering. Pytorch implementation for ECCV 2022 Paper “Self-Filtering: A Noise-Aware Sample Selection for Label Noise with Confidence Penalization”

SNSCL. Pytorch implementation for CVPR 2023 paper "Fine-Grianed Classification with Noisy Labels".

Multi-Level-MMD-Regularization. Enhancing Backdoor Attacks with Multi-Level MMD Regularization

pytorch_influence_functions. This is a PyTorch reimplementation of Influence Functions from the ICML2017 best paper: Understanding Black-box Predictions via Influence Functions by Pang Wei Koh and Percy Liang.

awesome-data-poisoning-and-backdoor-attacks. A curated list of papers & resources linked to data poisoning, backdoor attacks and defenses against them (no longer maintained)

MGAug. The implementation of the MGAug method.

DivideMix. Code for paper: DivideMix: Learning with Noisy Labels as Semi-supervised Learning

Learning-with-Noisy-Labels. A paper list (updated monthly) about learning with noisy labels.

SelfSup_NoisyLabel. Learning from noisy labels via regularization between representations

Entropy-selection. Pytorch implementation for SCIENTIA SINICA Informatioinis 2023 paper: A Joint Framework for Learning with Noisy Labels

AMS-M2ESL. [TGRS 2023] Official implementation for 'Adaptive Mask Sampling and Manifold to Euclidean Subspace Learning with Distance Covariance Representation for Hyperspectral Image Classification'

awesome-semi-supervised-learning. 😎 An up-to-date & curated list of awesome semi-supervised learning papers, methods & resources.

FaMUS. Python

MLC. Meta Label Correction for Noisy Label Learning

meta-weight-net. NeurIPS'19: Meta-Weight-Net: Learning an Explicit Mapping For Sample Weighting (Pytorch implementation for noisy labels).

comp. [NeurIPS 2017] [ICML 2019] Code for complementary-label learning

CVSSN. [TCSVT 2022] Official implementation for 'Exploring the Relationship between Center and Neighborhoods: Central Vector Oriented Self-Similarity Network for Hyperspectral Image Classification'

Advances-in-Partial-Label-Learning. A list of awesome partial-label learning papers and codes.

PiCO. PyTorch implementation of PiCO https://arxiv.org/abs/2201.08984