no code implementations • 17 Mar 2024 • Boshi Wang, Cunhua Pan, Hong Ren, Zhiyuan Yu, Yang Zhang, Mengyu Liu, Gui Zhou
Due to the signal amplification capability of active RISs, the mutual influence between active RISs, which is termed as the "inter-excitation" effect, cannot be ignored.
1 code implementation • 7 Mar 2024 • Boshi Wang, Hao Fang, Jason Eisner, Benjamin Van Durme, Yu Su
We find that existing LLMs, including GPT-4 and open-source LLMs specifically fine-tuned for tool use, only reach a correctness rate in the range of 30% to 60%, far from reliable use in practice.
no code implementations • 8 Feb 2024 • Yasheng Jin, Hong Ren, Cunhua Pan, Zhiyuan Yu, Ruisong Weng, Boshi Wang, Gui Zhou, Yongchao He, Maged Elkashlan
In this paper, we investigate an reconfigurable intelligent surface (RIS)-aided integrated sensing and communication (ISAC) system.
no code implementations • 7 Feb 2024 • Mengyu Liu, Hong Ren, Cunhua Pan, Boshi Wang, Zhiyuan Yu, Ruisong Weng, Kangda Zhi, Yongchao He
However, when radar and communication equipment coexist in the same system, i. e. radar-communication coexistence (RCC), the interference from communication systems to radar can be large and cannot be ignored.
no code implementations • 3 Feb 2024 • Yang Zhang, Hong Ren, Cunhua Pan, Boshi Wang, Zhiyuan Yu, Ruisong Weng, Tuo Wu, Yongchao He
This work considers a dual-functional radar and communication (DFRC) system with an active reconfigurable intelligent surface (RIS) and a potential eavesdropper.
1 code implementation • 15 Nov 2023 • Lingbo Mo, Boshi Wang, Muhao Chen, Huan Sun
The rapid progress in open-source Large Language Models (LLMs) is significantly driving AI development forward.
1 code implementation • NeurIPS 2023 • Xiang Deng, Yu Gu, Boyuan Zheng, Shijie Chen, Samuel Stevens, Boshi Wang, Huan Sun, Yu Su
We introduce Mind2Web, the first dataset for developing and evaluating generalist agents for the web that can follow language instructions to complete complex tasks on any website.
no code implementations • 22 May 2023 • Boshi Wang, Xiang Yue, Huan Sun
Large language models (LLMs) such as ChatGPT and GPT-4 have shown impressive performance in complex reasoning tasks.
1 code implementation • 10 May 2023 • Xiang Yue, Boshi Wang, Ziru Chen, Kai Zhang, Yu Su, Huan Sun
We manually curate a set of test examples covering 12 domains from a generative search engine, New Bing.
1 code implementation • IEEE International Conference on Big Data 2022 • Boshi Wang, Adrian Barbu
Incremental class learning is the classification problem of learning a model where instances from new object classes are added sequentially, and it is desired that the model be retrained only on the new classes with minimal training on the old classes.
Ranked #1 on Class Incremental Learning on CIFAR-100 - 50 classes + 10 steps of 5 classes (using extra training data)
2 code implementations • 20 Dec 2022 • Boshi Wang, Sewon Min, Xiang Deng, Jiaming Shen, You Wu, Luke Zettlemoyer, Huan Sun
Chain-of-Thought (CoT) prompting can dramatically improve the multi-step reasoning abilities of large language models (LLMs).
1 code implementation • 19 Dec 2022 • Vardaan Pahuja, Boshi Wang, Hugo Latapie, Jayanth Srinivasa, Yu Su
To address the limitations of existing KG link prediction frameworks, we propose a novel retrieve-and-read framework, which first retrieves a relevant subgraph context for the query and then jointly reasons over the context and the query with a high-capacity reader.
Ranked #2 on Link Prediction on FB15k-237
1 code implementation • 16 Mar 2022 • Boshi Wang, Xiang Deng, Huan Sun
While Pre-trained Language Models (PLMs) internalize a great amount of world knowledge, they have been shown incapable of recalling these knowledge to solve tasks requiring complex & multi-step reasoning.
no code implementations • ICLR 2022 • Boshi Wang, Jialin Yi, Hang Dong, Bo Qiao, Chuan Luo, QIngwei Lin
Combinatorial optimization problems with parameters to be predicted from side information are commonly seen in a variety of problems during the paradigm shift from reactive decision making to proactive decision making.