8 citations · 21 across the 8 of their papers we have counts for
9 papers
SAKE: Self-aware Knowledge Exploitation-Exploration for Grounded Multimodal Named Entity Recognition
Jielong Tang, Xujie Yuan, Jiayang Liu +6
Grounded Multimodal Named Entity Recognition (GMNER) aims to extract named entities and localize their visual regions within image-text pairs, serving as a pivotal capability for v…
LongCoder: A Long-Range Pre-trained Language Model for Code Completion
Daya Guo, Canwen Xu, Nan Duan +2
In this paper, we introduce a new task for code completion that focuses on handling long code input and propose a sparse Transformer model, called LongCoder, to address this task.…
Learning Profitable NFT Image Diffusions via Multiple Visual-Policy Guided Reinforcement Learning
Huiguo He, Tianfu Wang, Huan Yang +5
We study the task of generating profitable Non-Fungible Token (NFT) images from user-input texts. Recent advances in diffusion models have shown great potential for image generatio…
UniDiff: Advancing Vision-Language Models with Generative and Discriminative Learning
Xiao Dong, Runhui Huang, Xiaoyong Wei +4
Recent advances in vision-language pre-training have enabled machines to perform better in multimodal object discrimination (e.g., image-text semantic alignment) and image synthesi…
Disentangling Reasoning Capabilities from Language Models with Compositional Reasoning Transformers
Wanjun Zhong, Tingting Ma, Jiahai Wang +4
This paper presents ReasonFormer, a unified reasoning framework for mirroring the modular and compositional reasoning process of humans in complex decision-making. Inspired by dual…
Improving Task Generalization via Unified Schema Prompt
Wanjun Zhong, Yifan Gao, Ning Ding +5
Task generalization has been a long standing challenge in Natural Language Processing (NLP). Recent research attempts to improve the task generalization ability of pre-trained lang…
ProQA: Structural Prompt-based Pre-training for Unified Question Answering
Wanjun Zhong, Yifan Gao, Ning Ding +6
Question Answering (QA) is a longstanding challenge in natural language processing. Existing QA works mostly focus on specific question types, knowledge domains, or reasoning skill…
UniXcoder: Unified Cross-Modal Pre-training for Code Representation
Daya Guo, Shuai Lu, Nan Duan +3
Pre-trained models for programming languages have recently demonstrated great success on code intelligence. To support both code-related understanding and generation tasks, recent…
Learning to Complete Code with Sketches
Daya Guo, Alexey Svyatkovskiy, Jian Yin +3
Code completion is usually cast as a language modelling problem, i.e., continuing an input in a left-to-right fashion. However, in practice, some parts of the completion (e.g., str…