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This repository contains the replication materials for the paper MCGrad Multicalibration at Web Scale - to be presented at the KDD 2026 conference.
[KDD'2026] "TV-Diff: Towards A Tri-View Diffusion Framework for Recommendation"
The code repository for the KDD 2026 paper "Q-Regularized Generative Auto-Bidding: From Suboptimal Trajectories to Optimal Policies"
The code repository for the SIGIR 2026 paper "Generative Auto-Bidding with Unified Modeling and Exploration"
Curated list of modern recommendation system papers (2025-2026): LLM4Rec, Generative Recommendation, Token-based models
1
Updated Apr 30, 2026
Production-grade Rust-native trading engine with deterministic event-driven architecture
Efficient Infinite Context Transformers with Infini-attention Pytorch Implementation + QwenMoE Implementation + Training Script + 1M context keypass retrieval
中国软件著作权申请材料 生成器 Skills，本 Skills 通过阅读本地项目，自动生成全套 .docx 软著申请材料，全开源，无须再付费购买任何软著申请服务
CoSearch: Joint Training of Reasoning and Document Ranking via Reinforcement Learning for Agentic Search
This is the code for NeuralLoss: A Learnable Pretrained Surrogate Loss for Learning to Rank.
Based to the paper Interval Learning: Using Low-Rank Convolutions.
CreativeRank is a machine learning system designed to predict which email creative variations (images and subject lines) will perform best in A/B testing campaigns. The system uses LLM-based featur…
A Large-Scale Web Search Dataset for Federated Online Learning to Rank
Implementing learning-to-rank models with TensorFlow.
"OpenLoRa" is designed to streamline and elevate the fine-tuning of large language models (LLMs) by transforming local environments into intelligent, self-adaptive LoRA (Low-Rank Adaptation) traini…
Learning to Rank LLM Expertise for the TREC 2025 Million LLMs Track
1
Updated Apr 20, 2026
Search Ranking Model — Learning to Rank with LambdaMART
AlloyGBM is a Rust-first gradient boosting library with Python bindings, supporting regression, binary classification, and learning-to-rank. It is built for fast native execution, deterministic tra…
A large-scale robustness and stability analysis of learning-to-rank models under feature perturbations
Learning to rank (LTR) with noisy labels and simulation of how noise affects quality of ranking
Ecommerce-Search - Query Understanding, Spellcheck, Semantic Retrieval, Multimodal Fusion Embeddings, Faiss Index, Cross Encoder Reranker, LTR Reranker
Pet project for learn-to-rank inference optimization