Popular GitHub Repositories for Cold Mailing

推荐/广告/搜索领域工业界经典以及最前沿论文集合。A collection of industry classics and cutting-edge papers in the field of recommendation/advertising/search.

Power Tools for AI Engineers With Deadlines

Universal User Representation Pre-training for Cross-domain Recommendation and User Profiling

A curated list of resources on cold-start recommendations.

?ReVisual-R1 is a 7B open-source multimodal language model that follows a three-stage curriculum—cold-start pre-training, multimodal reinforcement learning, and text-only reinforcement learning—to achieve faithful, concise, and self-reflective state-of-the-art performance in visual and textual reasoning.

Cold Compress is a hackable, lightweight, and open-source toolkit for creating and benchmarking cache compression methods built on top of GPT-Fast, a simple, PyTorch-native generation codebase.

深度学习与推荐系统学习，理论结合代码更香。

Source code for the EMNLP 2020 paper "Cold-Start and Interpretability: Turning Regular Expressions intoTrainable Recurrent Neural Networks"

Code for Paper (Preserving Diversity in Supervised Fine-tuning of Large Language Models)

Source code for MetaKG: Meta-learning on Knowledge Graph for Cold-start Recommendation. TKDE 2022.

cross-domain recommendation，transfer learning，pre-training，self-supervise learning papers and datasets

EnergeticAI is TensorFlow.js, optimized for serverless environments, with fast cold-start, small module size, and pre-trained models.

Voice AI agent for reactivating cold leads through personalized calls, assessing their interest with AI agents, and syncing insights directly to your CRMs.

cold-mailing ai agent that takes in email address, recipient name, and other details to send mail.

[ACL 2023] The code for our ACL'23 paper Cold-Start Data Selection for Few-shot Language Model Fine-tuning: A Prompt-Based Uncertainty Propagation Approach

papers of universal user representation learning for recommendation

[ECIR 2024] Official repository for the paper titled "Self Contrastive Learning for Session-based Recommendation"

[ACL2018] Cold-Start Aware User and Product Attention for Sentiment Classification

Content-based Video Relevance Prediction on "cold-start" problems. Recommending new uploaded videos to users based on the extracted features.

Pre-training and Transfer learning papers for recommendation