collaborators

6 papers

cs.LG2026

Macaron-V1: Towards Open Continual Learning with Self-Improvement and Mixture-of-LoRA

Mind Lab, :, Vin Bo +74

Macaron-V1 is an open agent-model family for experiential intelligence: learning from experience in real environments and continuing to learn after deployment. It is organized arou…

cs.DL2026

MIRAI: Prediction and Generation of High-Impact Academic Research

Alex Li, Joseph Jacobson

The rapid pace of scientific publishing has made the identification and synthesis of high-impact work an increasingly urgent challenge. We introduce MIRAI (Multi-year Inference of…

cs.LG2026

On the Scaling of PEFT: Towards Million Personal Models of Trillion Parameters

Mind Lab, :, Vin Bo +64

Parameter-efficient fine-tuning (PEFT) is usually treated as a cheaper alternative to full fine-tuning. We study a broader role: small trainable adapters as persistent local state…

cs.LG2026

MinT: Managed Infrastructure for Training and Serving Millions of LLMs

Mind Lab, :, Song Cao +60

We present MindLab Toolkit (MinT), a managed infrastructure system for Low-Rank Adaptation (LoRA) post-training and online serving. MinT targets a setting where many trained polici…

cs.IR2026

Unified Learning-to-Rank for Multi-Channel Retrieval in Large-Scale E-Commerce Search

Aditya Gaydhani, Guangyue Xu, Dhanush Kamath +2

Large-scale e-commerce search must surface a broad set of items from a vast catalog, ranging from bestselling products to new, trending, or seasonal items. Modern systems therefore…

cs.IR2025

Large Scale Retrieval for the LinkedIn Feed using Causal Language Models

Sudarshan Srinivasa Ramanujam, Antonio Alonso, Saurabh Kataria +20

In large scale recommendation systems like the LinkedIn Feed, the retrieval stage is critical for narrowing hundreds of millions of potential candidates to a manageable subset for…