Search Results for author: Bin Lin

Found 8 papers, 4 papers with code

LLMBind: A Unified Modality-Task Integration Framework

no code implementations22 Feb 2024 Bin Zhu, Peng Jin, Munan Ning, Bin Lin, Jinfa Huang, Qi Song, Jiaxi Cui, Junwu Zhang, Zhenyu Tang, Mingjun Pan, Xing Zhou, Li Yuan

While recent progress in multimodal large language models tackles various modality tasks, they posses limited integration capabilities for complex multi-modality tasks, consequently constraining the development of the field.

Audio Generation Image Segmentation +1

Video-Bench: A Comprehensive Benchmark and Toolkit for Evaluating Video-based Large Language Models

1 code implementation27 Nov 2023 Munan Ning, Bin Zhu, Yujia Xie, Bin Lin, Jiaxi Cui, Lu Yuan, Dongdong Chen, Li Yuan

Video-based large language models (Video-LLMs) have been recently introduced, targeting both fundamental improvements in perception and comprehension, and a diverse range of user inquiries.

Decision Making Question Answering

Video-LLaVA: Learning United Visual Representation by Alignment Before Projection

4 code implementations16 Nov 2023 Bin Lin, Yang Ye, Bin Zhu, Jiaxi Cui, Munan Ning, Peng Jin, Li Yuan

In this work, we unify visual representation into the language feature space to advance the foundational LLM towards a unified LVLM.

Language Modelling Large Language Model +2

Operator Learning Enhanced Physics-informed Neural Networks for Solving Partial Differential Equations Characterized by Sharp Solutions

no code implementations30 Oct 2023 Bin Lin, Zhiping Mao, Zhicheng Wang, George Em Karniadakis

Initially, we utilize DeepONet to learn the solution operator for a set of smooth problems relevant to the PDEs characterized by sharp solutions.

Operator learning

Automated Identification of On-hold Self-admitted Technical Debt

no code implementations28 Sep 2020 Rungroj Maipradit, Bin Lin, Csaba Nagy, Gabriele Bavota, Michele Lanza, Hideaki Hata, Kenichi Matsumoto

Self-admitted technical debt (SATD) is a particular form of technical debt: developers consciously perform the hack but also document it in the code by adding comments as a reminder (or as an admission of guilt).

Software Engineering

Toward an Automated Auction Framework for Wireless Federated Learning Services Market

no code implementations13 Dec 2019 Yutao Jiao, Ping Wang, Dusit Niyato, Bin Lin, Dong In Kim

In this paper, we propose an auction based market model for incentivizing data owners to participate in federated learning.

Computer Science and Game Theory

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