# Overview of the TREC 2023 NeuCLIR Track

arXiv: https://arxiv.org/abs/2404.08071 · HTML: https://mlsanity.com/paper/2404.08071/

## Key facts

- Cited by 17 papers in the map (data through 7 Oct 2026).
- First posted on arXiv 11 Apr 2024.

## Built on by (most cited first, 17 of 17)

- [LLMs-as-Judges: A Comprehensive Survey on LLM-based Evaluation Methods](https://mlsanity.com/paper/2412.05579/) (2024)
- [INQUIRE: A Natural World Text-to-Image Retrieval Benchmark](https://mlsanity.com/paper/2411.02537/) (2024)
- [LaMP-QA: A Benchmark for Personalized Long-form Question Answering](https://mlsanity.com/paper/2506.00137/) (2025)
- [WikiVideo: Article Generation from Multiple Videos](https://mlsanity.com/paper/2504.00939/) (2025)
- [FaMTEB: Massive Text Embedding Benchmark in Persian Language](https://mlsanity.com/paper/2502.11571/) (2025)
- [Controlled Retrieval-augmented Context Evaluation for Long-form RAG](https://mlsanity.com/paper/2506.20051/) (2025)
- [Milco: Learned Sparse Retrieval Across Languages via a Multilingual Connector](https://mlsanity.com/paper/2510.00671/) (2025)
- [mFollowIR: a Multilingual Benchmark for Instruction Following in Retrieval](https://mlsanity.com/paper/2501.19264/) (2025)
- [PLAID SHIRTTT for Large-Scale Streaming Dense Retrieval](https://mlsanity.com/paper/2405.00975/) (2024)
- [Distillation for Multilingual Information Retrieval](https://mlsanity.com/paper/2405.00977/) (2024)
- [Examining Multilingual Embedding Models Cross-Lingually Through LLM-Generated Adversarial Examples](https://mlsanity.com/paper/2502.08638/) (2025)
- [CLIRudit: Cross-Lingual Information Retrieval of Scientific Documents](https://mlsanity.com/paper/2504.16264/) (2025)
- [Does Reasoning Make Search More Fair? Comparing Fairness in Reasoning and Non-Reasoning Rerankers](https://mlsanity.com/paper/2603.10332/) (2026)
- [Shaping the Future of Endangered and Low-Resource Languages -- Our Role in the Age of LLMs: A Keynote at ECIR 2024](https://mlsanity.com/paper/2409.13702/) (2024)
- [Seeing Through the MiRAGE: Evaluating Multimodal Retrieval Augmented Generation](https://mlsanity.com/paper/2510.24870/) (2025)
- [RoutIR: Fast Serving of Retrieval Pipelines for Retrieval-Augmented Generation](https://mlsanity.com/paper/2601.10644/) (2026)
- [MIMO: Multilingual Information Retrieval via Monolingual Objectives](https://mlsanity.com/paper/2605.31171/) (2026)

## Abstract (arXiv)

The principal goal of the TREC Neural Cross-Language Information Retrieval (NeuCLIR) track is to study the impact of neural approaches to cross-language information retrieval. The track has created four collections, large collections of Chinese, Persian, and Russian newswire and a smaller collection of Chinese scientific abstracts. The principal tasks are ranked retrieval of news in one of the three languages, using English topics. Results for a multilingual task, also with English topics but with documents from all three newswire collections, are also reported. New in this second year of the track is a pilot technical documents CLIR task for ranked retrieval of Chinese technical documents using English topics. A total of 220 runs across all tasks were submitted by six participating teams and, as baselines, by track coordinators. Task descriptions and results are presented.