Long-RL: Scaling RL to Long Sequences (NeurIPS 2025)

Survey: https://arxiv.org/pdf/2507.20198

A High-Efficiency System of Large Language Model Based Search Agents

Official Repo for SparseLLM: Global Pruning of LLMs (NeurIPS 2024)

Official PyTorch implementation of the paper "Dataset Distillation via the Wasserstein Metric" (ICCV 2025).

TinyML and Efficient Deep Learning Computing | MIT 6.S965/6.5940

Dynamic Attention Mask (DAM) generate adaptive sparse attention masks per layer and head for Transformer models, enabling long-context inference with lower compute and memory overhead without fine-tuning.

A deep learning framework that implements Early Exit strategies in Convolutional Neural Networks (CNNs) using Deep Q-Learning (DQN). This project enhances computational efficiency by dynamically determining the optimal exit point in a neural network for image classification tasks on CIFAR-10.

Code for paper "Automated Design for Hardware-aware Graph Neural Networks on Edge Devices"

MOCA-Net: Novel neural architecture with sparse MoE, external memory, and budget-aware computation. Real Stanford SST-2 integration, O(L) complexity, 96.40% accuracy. Built for efficient sequence modeling.

In this repo you will understand .The process of reducing the precision of a model’s parameters and/or activations (e.g., from 32-bit floating point to 8-bit integers) to make neural networks smaller, faster, and more energy-efficient with minimal accuracy loss.

Task-Aware Dynamic Model Optimization for Multi-Task Learning (IEEE Access 2023)

Production-grade GPT transformer implemented from scratch in C++. Runs on modest hardware with complete mathematical derivations and optimized tensor operations.

QuantLab-8bit is a reproducible benchmark of 8-bit quantization on compact vision backbones. It includes FP32 baselines, PTQ (dynamic & static), QAT, ONNX exports, parity checks, ORT CPU latency, and visual diagnostics.