1 code implementation • ECCV 2020 • Xuefeng Hu, Zhihan Zhang, Zhenye Jiang, Syomantak Chaudhuri, Zhenheng Yang, Ram Nevatia
Tehchniques for manipulating images are advancing rapidly; while these are helpful for many useful tasks, they also pose a threat to society with their ability to create believable misinformation.
Ranked #5 on Image Manipulation Localization on Columbia
no code implementations • 1 May 2024 • Zhihan Zhang, Weiyuan Gong, Weikang Li, Dong-Ling Deng
In addition, for quantum devices with constant noise strength, we prove that no super-polynomial classical-quantum separation exists for any classification task defined by shallow Clifford circuits, independent of the structures of the circuits that specify the learning models.
no code implementations • 22 Apr 2024 • Mengzhao Jia, Zhihan Zhang, Wenhao Yu, Fangkai Jiao, Meng Jiang
Open-source multimodal large language models (MLLMs) excel in various tasks involving textual and visual inputs but still struggle with complex multimodal mathematical reasoning, lagging behind proprietary models like GPT-4V(ision) and Gemini-Pro.
1 code implementation • 14 Mar 2024 • Chu Li, Zhihan Zhang, Michael Saugstad, Esteban Safranchik, Minchu Kulkarni, Xiaoyu Huang, Shwetak Patel, Vikram Iyer, Tim Althoff, Jon E. Froehlich
Crowdsourcing platforms have transformed distributed problem-solving, yet quality control remains a persistent challenge.
1 code implementation • 12 Feb 2024 • Qingkai Zeng, Yuyang Bai, Zhaoxuan Tan, Shangbin Feng, Zhenwen Liang, Zhihan Zhang, Meng Jiang
Automatic taxonomy induction is crucial for web search, recommendation systems, and question answering.
1 code implementation • 15 Nov 2023 • Zhihan Zhang, Dong-Ho Lee, Yuwei Fang, Wenhao Yu, Mengzhao Jia, Meng Jiang, Francesco Barbieri
Instruction tuning has remarkably advanced large language models (LLMs) in understanding and responding to diverse human instructions.
no code implementations • 19 Oct 2023 • Zhihan Zhang, Shuohang Wang, Wenhao Yu, Yichong Xu, Dan Iter, Qingkai Zeng, Yang Liu, Chenguang Zhu, Meng Jiang
Large language models (LLMs) can perform a wide range of tasks by following natural language instructions, without the necessity of task-specific fine-tuning.
no code implementations • 7 Jul 2023 • Zachary Englhardt, Richard Li, Dilini Nissanka, Zhihan Zhang, Girish Narayanswamy, Joseph Breda, Xin Liu, Shwetak Patel, Vikram Iyer
We leverage this finding to study how human programmers interact with these tools, and develop an human-AI based software engineering workflow for building embedded systems.
no code implementations • 23 May 2023 • Wenhao Yu, Zhihan Zhang, Zhenwen Liang, Meng Jiang, Ashish Sabharwal
ReFeed first generates initial outputs, then utilizes a retrieval model to acquire relevant information from large document collections, and finally incorporates the retrieved information into the in-context demonstration for output refinement, thereby addressing the limitations of LLMs in a more efficient and cost-effective manner.
1 code implementation • 23 May 2023 • Zhihan Zhang, Wenhao Yu, Zheng Ning, Mingxuan Ju, Meng Jiang
Contrast consistency, the ability of a model to make consistently correct predictions in the presence of perturbations, is an essential aspect in NLP.
no code implementations • 23 May 2023 • Mengxia Yu, Zhihan Zhang, Wenhao Yu, Meng Jiang
Comparative reasoning is a process of comparing objects, concepts, or entities to draw conclusions, which constitutes a fundamental cognitive ability.
1 code implementation • 16 May 2023 • Noah Ziems, Wenhao Yu, Zhihan Zhang, Meng Jiang
To overcome this limitation, recent autoregressive search engines replace the dual-encoder architecture by directly generating identifiers for relevant documents in the candidate pool.
4 code implementations • 9 May 2023 • Raymond Li, Loubna Ben allal, Yangtian Zi, Niklas Muennighoff, Denis Kocetkov, Chenghao Mou, Marc Marone, Christopher Akiki, Jia Li, Jenny Chim, Qian Liu, Evgenii Zheltonozhskii, Terry Yue Zhuo, Thomas Wang, Olivier Dehaene, Mishig Davaadorj, Joel Lamy-Poirier, João Monteiro, Oleh Shliazhko, Nicolas Gontier, Nicholas Meade, Armel Zebaze, Ming-Ho Yee, Logesh Kumar Umapathi, Jian Zhu, Benjamin Lipkin, Muhtasham Oblokulov, Zhiruo Wang, Rudra Murthy, Jason Stillerman, Siva Sankalp Patel, Dmitry Abulkhanov, Marco Zocca, Manan Dey, Zhihan Zhang, Nour Fahmy, Urvashi Bhattacharyya, Wenhao Yu, Swayam Singh, Sasha Luccioni, Paulo Villegas, Maxim Kunakov, Fedor Zhdanov, Manuel Romero, Tony Lee, Nadav Timor, Jennifer Ding, Claire Schlesinger, Hailey Schoelkopf, Jan Ebert, Tri Dao, Mayank Mishra, Alex Gu, Jennifer Robinson, Carolyn Jane Anderson, Brendan Dolan-Gavitt, Danish Contractor, Siva Reddy, Daniel Fried, Dzmitry Bahdanau, Yacine Jernite, Carlos Muñoz Ferrandis, Sean Hughes, Thomas Wolf, Arjun Guha, Leandro von Werra, Harm de Vries
The BigCode community, an open-scientific collaboration working on the responsible development of Large Language Models for Code (Code LLMs), introduces StarCoder and StarCoderBase: 15. 5B parameter models with 8K context length, infilling capabilities and fast large-batch inference enabled by multi-query attention.
Ranked #43 on Code Generation on MBPP
1 code implementation • 23 Oct 2022 • Wenhao Yu, Chenguang Zhu, Zhihan Zhang, Shuohang Wang, Zhuosheng Zhang, Yuwei Fang, Meng Jiang
However, applying such methods to commonsense reasoning tasks faces two unique challenges, i. e., the lack of a general large-scale corpus for retrieval and a corresponding effective commonsense retriever.
1 code implementation • 7 Oct 2022 • Zhihan Zhang, Wenhao Yu, Chenguang Zhu, Meng Jiang
The entity knowledge is stored in the memory as latent representations, and the memory is pre-trained on Wikipedia along with encoder-decoder parameters.
no code implementations • 9 Jul 2022 • Gang Liu, Zhihan Zhang, Zheng Ning, Meng Jiang
To enable explainability, recent techniques such as ACCENT and FIA are looking for counterfactual explanations that are specific historical actions of a user, the removal of which leads to a change to the recommendation result.
no code implementations • 7 Apr 2022 • Zhihan Zhang, Wenhao Yu, Mengxia Yu, Zhichun Guo, Meng Jiang
Multi-task learning (MTL) has become increasingly popular in natural language processing (NLP) because it improves the performance of related tasks by exploiting their commonalities and differences.
1 code implementation • NAACL (DLG4NLP) 2022 • Wenhao Yu, Chenguang Zhu, Lianhui Qin, Zhihan Zhang, Tong Zhao, Meng Jiang
A set of knowledge experts seek diverse reasoning on KG to encourage various generation outputs.
no code implementations • 28 Sep 2020 • Zhihan Zhang, Xiubo Geng, Tao Qin, Yunfang Wu, Daxin Jiang
In this work, we focus on the task of procedural text understanding, which aims to comprehend such documents and track entities' states and locations during a process.
no code implementations • 1 Sep 2020 • Xuefeng Hu, Zhihan Zhang, Zhenye Jiang, Syomantak Chaudhuri, Zhenheng Yang, Ram Nevatia
We present a novel framework, Spatial Pyramid Attention Network (SPAN) for detection and localization of multiple types of image manipulations.
1 code implementation • 25 Jul 2020 • Daheng Wang, Zhihan Zhang, Yihong Ma, Tong Zhao, Tianwen Jiang, Nitesh V. Chawla, Meng Jiang
In this work, we present a novel framework called CoEvoGNN for modeling dynamic attributed graph sequence.
no code implementations • 7 Nov 2019 • Zhihan Zhang, Zhiyi Yin, Shuhuai Ren, Xinhang Li, Shicheng Li
In this paper, we aim to collect diversified information from video and text for informative comment generation.
1 code implementation • ACL 2019 • Pengcheng Yang, Zhihan Zhang, Fuli Luo, Lei LI, Chengyang Huang, Xu sun
Automatic commenting of online articles can provide additional opinions and facts to the reader, which improves user experience and engagement on social media platforms.