activity
20162023
most citedSelf-Attention Networks for Connectionist Temporal Classification in Speech Recognition

133 citations · 308 across the 15 of their papers we have counts for

collaborators

20 papers

cond-mat.mtrl-sci2023★ 47 cited

Weyl phonons in chiral crystals

Tiantian Zhang, Zhiheng Huang, Zitian Pan +3

Chirality is an indispensable concept that pervades fundamental science and nature, manifesting itself in diverse forms such as chiral quasiparticles and chiral structures. Of part…

physics.optics2023★ 2 cited

Electron-infrared phonon coupling in ABC trilayer graphene

Xiaozhou Zan, Xiangdong Guo, Aolin Deng +18

Stacking order plays a crucial role in determining the crystal symmetry and has significant impacts on electronic, optical, magnetic, and topological properties. Electron-phonon co…

cs.CL2023★ 6 cited

STREET: A Multi-Task Structured Reasoning and Explanation Benchmark

Danilo Ribeiro, Shen Wang, Xiaofei Ma +10

We introduce STREET, a unified multi-task and multi-domain natural language reasoning and explanation benchmark. Unlike most existing question-answering (QA) datasets, we expect mo…

cs.CL2022

Improving Cross-task Generalization of Unified Table-to-text Models with Compositional Task Configurations

Jifan Chen, Yuhao Zhang, Lan Liu +5

There has been great progress in unifying various table-to-text tasks using a single encoder-decoder model trained via multi-task learning (Xie et al., 2022). However, existing met…

cs.CL2022★ 2 cited

Tokenization Consistency Matters for Generative Models on Extractive NLP Tasks

Kaiser Sun, Peng Qi, Yuhao Zhang +3

Generative models have been widely applied to solve extractive tasks, where parts of the input is extracted to form the desired output, and achieved significant success. For exampl…

cs.IR2022★ 1 cited

Language Agnostic Multilingual Information Retrieval with Contrastive Learning

Xiyang Hu, Xinchi Chen, Peng Qi +4

Multilingual information retrieval (IR) is challenging since annotated training data is costly to obtain in many languages. We present an effective method to train multilingual IR…