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20212026
most citedLarge Language Models are not Fair Evaluators

33 citations · 77 across the 29 of their papers we have counts for

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10 papers · 1 filter

cs.CL2025★ 2 cited

MiMo-Audio: Audio Language Models are Few-Shot Learners

Core Team, Dong Zhang, Gang Wang +97

Existing audio language models typically rely on task-specific fine-tuning to accomplish particular audio tasks. In contrast, humans are able to generalize to new audio tasks with…

cs.CV2025

DocLens : A Tool-Augmented Multi-Agent Framework for Long Visual Document Understanding

Dawei Zhu, Rui Meng, Jiefeng Chen +3

Comprehending long visual documents, where information is distributed across extensive pages of text and visual elements, is a critical but challenging task for modern Vision-Langu…

cs.CL2025

Router Upcycling: Leveraging Mixture-of-Routers in Mixture-of-Experts Upcycling

Junfeng Ran, Guangxiang Zhao, Yuhan Wu +7

The Mixture-of-Experts (MoE) models have gained significant attention in deep learning due to their dynamic resource allocation and superior performance across diverse tasks. Howev…

cs.CL2025

Hierarchical Memory Organization for Wikipedia Generation

Eugene J. Yu, Dawei Zhu, Yifan Song +6

Generating Wikipedia articles autonomously is a challenging task requiring the integration of accurate, comprehensive, and well-structured information from diverse sources. This pa…

cs.CL2025★ 1 cited

MiMo: Unlocking the Reasoning Potential of Language Model -- From Pretraining to Posttraining

LLM-Core Xiaomi, :, Bingquan Xia +62

We present MiMo-7B, a large language model born for reasoning tasks, with optimization across both pre-training and post-training stages. During pre-training, we enhance the data p…

cs.CL2025

MiMo-VL Technical Report

Core Team, Zihao Yue, Zhenru Lin +71

We open-source MiMo-VL-7B-SFT and MiMo-VL-7B-RL, two powerful vision-language models delivering state-of-the-art performance in both general visual understanding and multimodal rea…

cs.CL2025★ 2 cited

A Comprehensive Survey on Long Context Language Modeling

Jiaheng Liu, Dawei Zhu, Zhiqi Bai +34

Efficient processing of long contexts has been a persistent pursuit in Natural Language Processing. With the growing number of long documents, dialogues, and other textual data, it…

cs.CL2025

Chain-of-Thought Matters: Improving Long-Context Language Models with Reasoning Path Supervision

Dawei Zhu, Xiyu Wei, Guangxiang Zhao +7

Recent advances in Large Language Models (LLMs) have highlighted the challenge of handling long-context tasks, where models need to reason over extensive input contexts to aggregat…

cs.CL2025

LongAttn: Selecting Long-context Training Data via Token-level Attention

Longyun Wu, Dawei Zhu, Guangxiang Zhao +5

With the development of large language models (LLMs), there has been an increasing need for significant advancements in handling long contexts. To enhance long-context capabilities…

cs.CL2025★ 15 cited

MMTEB: Massive Multilingual Text Embedding Benchmark

Kenneth Enevoldsen, Isaac Chung, Imene Kerboua +83

Text embeddings are typically evaluated on a limited set of tasks, which are constrained by language, domain, and task diversity. To address these limitations and provide a more co…