mlsanityData to 7 Oct 2026

Tele-FLM Technical Report

arXiv 2404.16645 ↗First posted 25 Apr 2024cs.CL cs.AIcited by 12

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Abstract (arXiv)

Large language models (LLMs) have showcased profound capabilities in language understanding and generation, facilitating a wide array of applications. However, there is a notable paucity of detailed, open-sourced methodologies on efficiently scaling LLMs beyond 50 billion parameters with minimum trial-and-error cost and computational resources. In this report, we introduce Tele-FLM (aka FLM-2), a 52B open-sourced multilingual large language model that features a stable, efficient pre-training paradigm and enhanced factual judgment capabilities. Tele-FLM demonstrates superior multilingual language modeling abilities, measured by BPB on textual corpus. Besides, in both English and Chinese foundation model evaluation, it is comparable to strong open-sourced models that involve larger pre-training FLOPs, such as Llama2-70B and DeepSeek-67B. In addition to the model weights, we share the core designs, engineering practices, and training details, which we expect to benefit both the academic and industrial communities.

Key facts. Cited by 12 papers in the map (data through 7 Oct 2026). Builds on 61 of its 78 references that are in the map. First posted on arXiv 25 Apr 2024.

Builds on

61 of 78 references.

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38 more
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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 3; 2025: 8; 2026: 1.

12 papers.