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Neural Scaling Laws for Embodied AI

S Sartor, N Thompson - arXiv preprint arXiv:2405.14005, 2024 - arxiv.org
Scaling laws have driven remarkable progress across machine learning domains like
language modeling and computer vision. However, the exploration of scaling laws in …
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Mitigating Entity-Level Hallucination in Large Language Models

W Su, Y Tang, Q Ai, C Wang, Z Wu, Y Liu - arXiv preprint arXiv:2407.09417, 2024 - arxiv.org
The emergence of Large Language Models (LLMs) has revolutionized how users access
information, shifting from traditional search engines to direct question-and-answer …
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Leveraging Passage Embeddings for Efficient Listwise Reranking with Large Language Models

Q Liu, B Wang, N Wang, J Mao - arXiv preprint arXiv:2406.14848, 2024 - arxiv.org
Recent studies have demonstrated the effectiveness of using large language language
models (LLMs) in passage ranking. The listwise approaches, such as RankGPT, have …
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STARD: A Chinese Statute Retrieval Dataset with Real Queries Issued by Non-professionals

W Su, Y Hu, A Xie, Q Ai, Z Que, N Zheng, Y Liu… - arXiv preprint arXiv …, 2024 - arxiv.org
Statute retrieval aims to find relevant statutory articles for specific queries. This process is the
basis of a wide range of legal applications such as legal advice, automated judicial …
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LeKUBE: A Legal Knowledge Update BEnchmark

C Wang, W Su, H Yiran, Q Ai, Y Wu, C Luo… - arXiv preprint arXiv …, 2024 - arxiv.org
Recent advances in Large Language Models (LLMs) have significantly shaped the
applications of AI in multiple fields, including the studies of legal intelligence. Trained on …
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