168 citations · 523 across the 46 of their papers we have counts for
14 papers · 1 filter
Dialogue Shaping: Empowering Agents through NPC Interaction
Wei Zhou, Xiangyu Peng, Mark Riedl
One major challenge in reinforcement learning (RL) is the large amount of steps for the RL agent needs to converge in the training process and learn the optimal policy, especially…
Manipulation of ray polarization in Compton scattering
Yu Wang, Mamutjan Ababekri, Feng Wan +8
High-brilliance high-polarization rays based on Compton scattering are of great significance in broad areas, such as nuclear, high-energy, astro-physics, etc. However, the tran…
Supervised Adversarial Contrastive Learning for Emotion Recognition in Conversations
Dou Hu, Yinan Bao, Lingwei Wei +2
Extracting generalized and robust representations is a major challenge in emotion recognition in conversations (ERC). To address this, we propose a supervised adversarial contrasti…
UCAS-IIE-NLP at SemEval-2023 Task 12: Enhancing Generalization of Multilingual BERT for Low-resource Sentiment Analysis
Dou Hu, Lingwei Wei, Yaxin Liu +2
This paper describes our system designed for SemEval-2023 Task 12: Sentiment analysis for African languages. The challenge faced by this task is the scarcity of labeled data and li…
Deep learning inter-atomic potential for irradiation damage in 3C-SiC
Yong Liu, Hao Wang, Linxin Guo +4
We developed and validated an accurate inter-atomic potential for molecular dynamics simulation in cubic silicon carbide (3C-SiC) using a deep learning framework combined with smoo…
Farewell to Aimless Large-scale Pretraining: Influential Subset Selection for Language Model
Xiao Wang, Weikang Zhou, Qi Zhang +7
Pretrained language models have achieved remarkable success in various natural language processing tasks. However, pretraining has recently shifted toward larger models and larger…
Stylized Data-to-Text Generation: A Case Study in the E-Commerce Domain
Liqiang Jing, Xuemeng Song, Xuming Lin +3
Existing data-to-text generation efforts mainly focus on generating a coherent text from non-linguistic input data, such as tables and attribute-value pairs, but overlook that diff…
PaLM 2 Technical Report
Rohan Anil, Andrew M. Dai, Orhan Firat +125
We introduce PaLM 2, a new state-of-the-art language model that has better multilingual and reasoning capabilities and is more compute-efficient than its predecessor PaLM. PaLM 2 i…
Galaxy Morphology Classification Using Multi-Scale Convolution Capsule Network
Guangping Li, Tingting Xu, Liping Li +5
The classification of galaxy morphology is a hot issue in astronomical research. Although significant progress has been made in the last decade in classifying galaxy morphology usi…
Towards Zero-Shot Personalized Table-to-Text Generation with Contrastive Persona Distillation
Haolan Zhan, Xuming Lin, Shaobo Cui +3
Existing neural methods have shown great potentials towards generating informative text from structured tabular data as well as maintaining high content fidelity. However, few of t…
InstructUIE: Multi-task Instruction Tuning for Unified Information Extraction
Xiao Wang, Weikang Zhou, Can Zu +11
Large language models have unlocked strong multi-task capabilities from reading instructive prompts. However, recent studies have shown that existing large models still have diffic…
JCDNet: Joint of Common and Definite phases Network for Weakly Supervised Temporal Action Localization
Yifu Liu, Xiaoxia Li, Zhiling Luo +1
Weakly-supervised temporal action localization aims to localize action instances in untrimmed videos with only video-level supervision. We witness that different actions record com…
BrainCLIP: Bridging Brain and Visual-Linguistic Representation Via CLIP for Generic Natural Visual Stimulus Decoding
Yulong Liu, Yongqiang Ma, Wei Zhou +2
Due to the lack of paired samples and the low signal-to-noise ratio of functional MRI (fMRI) signals, reconstructing perceived natural images or decoding their semantic contents fr…
Story Shaping: Teaching Agents Human-like Behavior with Stories
Xiangyu Peng, Christopher Cui, Wei Zhou +2
Reward design for reinforcement learning agents can be difficult in situations where one not only wants the agent to achieve some effect in the world but where one also cares about…