Zobrazeno 1 - 10
of 2 602
pro vyhledávání: '"Wang, Yulong"'
Autor:
Sasaki, Yuya, Wang, Yulong
We introduce a novel method for estimating and conducting inference about extreme quantile treatment effects (QTEs) in the presence of endogeneity. Our approach is applicable to a broad range of empirical research designs, including instrumental vari
Externí odkaz:
http://arxiv.org/abs/2409.03979
Existing agents based on large language models (LLMs) demonstrate robust problem-solving capabilities by integrating LLMs' inherent knowledge, strong in-context learning and zero-shot capabilities, and the use of tools combined with intricately desig
Externí odkaz:
http://arxiv.org/abs/2407.10718
Autor:
Yu, Yingpeng, Liu, Zhaolong, Li, Qi, Chen, Zhaoxu, Wang, Yulong, Hao, Munan, Yang, Yaling, Gong, Chunsheng, Chen, Long, Xie, Zhenkai, Zhou, Kaiyao, Ren, Huifen, Chen, Xu, Jin, Shifeng
We present a comprehensive investigation of the superconducting properties of ZrRe2, a Re-based hexagonal Laves compounds. ZrRe2 crystallizes in a C14-type structure (space group P63/mmc), with cell parameters a=b=5.2682(5) and c=8.63045 . Resistivit
Externí odkaz:
http://arxiv.org/abs/2407.10268
Autor:
Ju, Tianjie, Wang, Yiting, Ma, Xinbei, Cheng, Pengzhou, Zhao, Haodong, Wang, Yulong, Liu, Lifeng, Xie, Jian, Zhang, Zhuosheng, Liu, Gongshen
The rapid adoption of large language models (LLMs) in multi-agent systems has highlighted their impressive capabilities in various applications, such as collaborative problem-solving and autonomous negotiation. However, the security implications of t
Externí odkaz:
http://arxiv.org/abs/2407.07791
Autor:
Lv, Ang, Chen, Yuhan, Zhang, Kaiyi, Wang, Yulong, Liu, Lifeng, Wen, Ji-Rong, Xie, Jian, Yan, Rui
In this paper, we delve into several mechanisms employed by Transformer-based language models (LLMs) for factual recall tasks. We outline a pipeline consisting of three major steps: (1) Given a prompt ``The capital of France is,'' task-specific atten
Externí odkaz:
http://arxiv.org/abs/2403.19521
Neural implicit representation of geometric shapes has witnessed considerable advancements in recent years. However, common distance field based implicit representations, specifically signed distance field (SDF) for watertight shapes or unsigned dist
Externí odkaz:
http://arxiv.org/abs/2403.01414
Motivated by the empirical power law of the distributions of credits (e.g., the number of "likes") of viral posts in social media, we introduce the high-dimensional tail index regression and methods of estimation and inference for its parameters. We
Externí odkaz:
http://arxiv.org/abs/2403.01318
Large language models (LLMs) have played a pivotal role in building communicative AI to imitate human behaviors but face the challenge of efficient customization. To tackle this challenge, recent studies have delved into the realm of model editing, w
Externí odkaz:
http://arxiv.org/abs/2402.05827
Autor:
Bugni, Federico A., Wang, Yulong
This paper considers inference in first-price and second-price sealed-bid auctions in empirical settings where we observe auctions with a large number of bidders. Relevant applications include online auctions, treasury auctions, spectrum auctions, ar
Externí odkaz:
http://arxiv.org/abs/2311.09972
Publikováno v:
The Electronic Library, 2024, Vol. 42, Issue 5, pp. 741-765.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/EL-12-2023-0310