Search Results for author:
Found 13 papers, 9 papers with code
Meta-KD: A Meta Knowledge Distillation Framework for Language Model Compression across Domains
However, the large model sizes, together with the long inference time, limit the deployment of such models in real-time applications.
KwaiAgents: Generalized Information-seeking Agent System with Large Language Models
Driven by curiosity, humans have continually sought to explore and understand the world around them, leading to the invention of various tools to satiate this inquisitiveness.
ASER: A Large-scale Eventuality Knowledge Graph
Understanding human's language requires complex world knowledge.
ASER: Towards Large-scale Commonsense Knowledge Acquisition via Higher-order Selectional Preference over Eventualities
After conceptualization with Probase, a selectional preference based concept-instance relational knowledge base, our concept graph contains 15 million conceptualized eventualities and 224 million edges between them.
Kuaipedia: a Large-scale Multi-modal Short-video Encyclopedia
In this paper, we propose Kuaipedia, a large-scale multi-modal encyclopedia consisting of items, aspects, and short videos lined to them, which was extracted from billions of videos of Kuaishou (Kwai), a well-known short-video platform in China.
Neural Subgraph Isomorphism Counting
In this paper, we study a new graph learning problem: learning to count subgraph isomorphisms.
CogGPT: Unleashing the Power of Cognitive Dynamics on Large Language Models
Cognitive dynamics are pivotal to advance human understanding of the world.
Beyond Personalization: Social Content Recommendation for Creator Equality and Consumer Satisfaction
An effective content recommendation in modern social media platforms should benefit both creators to bring genuine benefits to them and consumers to help them get really interesting content.
Do Boat and Ocean Suggest Beach? Dialogue Summarization with External Knowledge
To evaluate the inference capability of different methods, we also propose a new evaluation metric based on CODC.
Dial2Desc: End-to-end Dialogue Description Generation
We first propose a new task named Dialogue Description (Dial2Desc).
Learning to Expand: Reinforced Pseudo-relevance Feedback Selection for Information-seeking Conversations
More specifically, we propose a reinforced selector to extract useful PRF terms to enhance response candidates and a BERT-based response ranker to rank the PRF-enhanced responses.
Meta Distant Transfer Learning for Pre-trained Language Models
For tasks related to distant domains with different class label sets, PLMs may memorize non-transferable knowledge for the target domain and suffer from negative transfer.
A Unified Model for Video Understanding and Knowledge Embedding with Heterogeneous Knowledge Graph Dataset
Furthermore, based on this dataset, we propose an end-to-end model that jointly optimizes the video understanding objective with knowledge graph embedding, which can not only better inject factual knowledge into video understanding but also generate effective multi-modal entity embedding for KG.
