# #papers — MDRSS hashtag feed

> Public MDRSS cards tagged #papers.
> Canonical feed: https://mdrss.com/feeds/papers

## Cards (7)

### [Must-read Papers on Legal Intelligence](https://mdrss.com/data-research/research-and-evaluation/901119/901119.md)

1. How Does NLP Benefit Legal System: A Summary of Legal Artificial Intelligence. Use it to build a structured path from fundamentals to hands-on practice.

Classification: data-research/research-and-evaluation · Feed: data-research · Updated: 2026-08-04T13:54:51.641Z · Version: 1

### [Awesome Meta Learning](https://mdrss.com/data-research/research-and-evaluation/901116/901116.md)

A curated list of Meta Learning papers, code, books, blogs, videos, datasets and other resources. Use it to navigate the topic and choose relevant methods, papers or tools.

Classification: data-research/research-and-evaluation · Feed: data-research · Updated: 2026-08-04T13:54:51.641Z · Version: 1

### [Machine Learning for Software Engineering](https://mdrss.com/data-research/research-and-evaluation/901109/901109.md)

This repository contains a curated list of papers, PhD theses, datasets, and tools that are devoted to research on Machine Learning for Software Engineering. The papers are organized into popular research areas so that researchers can find recent papers and state-of-the-art appro. Use it to build a structured path from fundamentals to hands-on practice.

Classification: data-research/research-and-evaluation · Feed: data-research · Updated: 2026-08-04T13:54:51.641Z · Version: 1

### [Awesome Audio-Visual](https://mdrss.com/multimodal/audio-music/901082/901082.md)

A curated list of papers and datsets for various audio-visual tasks, inspired by awesome-computer-vision. Use it to navigate the topic and choose relevant methods, papers or tools.

Classification: multimodal/audio-music · Feed: multimodal · Updated: 2026-08-04T13:54:51.641Z · Version: 1

### [Awesome Model Quantization](https://mdrss.com/llm-engineering/inference-and-quantization/901001/901001.md)

This repo collects papers, documents, and codes about model quantization for anyone who wants to research it. We are continuously improving the project. Use it to navigate the topic and choose relevant methods, papers or tools.

Classification: llm-engineering/inference-and-quantization · Feed: llm-engineering · Updated: 2026-08-04T13:54:51.641Z · Version: 1

### [A Watermark for Large Language Models](https://mdrss.com/learning/curricula-and-careers/2101/2101.md)

The WatermarkLogitsProcessor is designed to be readily compatible with any model that supports the generate API. Any model that can be constructed using the AutoModelForCausalLM or AutoModelForSeq2SeqLM factories should be compatible.

Classification: learning/curricula-and-careers · Feed: learning · Updated: 2026-08-04T12:22:38.168Z · Version: 1

### [Deep Learning for Mathematical Reasoning (DL4MATH)](https://mdrss.com/llm-engineering/evaluation/1284/1284.md)

This repository is the reading list on Deep Learning for Mathematical Reasoning (DL4MATH). Contributors: Pan Lu @UCLA, Liang Qiu @UCLA, Wenhao Yu @Notre Dame, Sean Welleck @UW, Kai-Wei Chang @UCLA For more details, please refer to the paper: A Survey of Deep Learning for Mathematical Reasoning.

Classification: llm-engineering/evaluation · Feed: llm-engineering · Updated: 2026-08-04T12:22:38.168Z · Version: 1