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Found 7 papers, 3 papers with code
Compression Represents Intelligence Linearly
We open-source our compression datasets as well as our data collection pipelines to facilitate future researchers to assess compression properly.
MeKB-Rec: Personal Knowledge Graph Learning for Cross-Domain Recommendation
Then we learn a semantic representation of MeKB for the cross-domain recommendation.
Retrieval-based Knowledge Augmented Vision Language Pre-training
With the recent progress in large-scale vision and language representation learning, Vision Language Pre-training (VLP) models have achieved promising improvements on various multi-modal downstream tasks.
Hansel: A Chinese Few-Shot and Zero-Shot Entity Linking Benchmark
We then establish a strong baseline that scores a R@1 of 46. 2% on Few-Shot and 76. 6% on Zero-Shot on our dataset.
Entity Linking in 100 Languages
We propose a new formulation for multilingual entity linking, where language-specific mentions resolve to a language-agnostic Knowledge Base.
Ranked #1 on
Entity Disambiguation
on Mewsli-9
(using extra training data)
Learning Cross-Context Entity Representations from Text
Language modeling tasks, in which words, or word-pieces, are predicted on the basis of a local context, have been very effective for learning word embeddings and context dependent representations of phrases.
Ranked #1 on
Entity Linking
on CoNLL-Aida
Feature Engineering for Knowledge Base Construction
Our approach to KBC is based on joint probabilistic inference and learning, but we do not see inference as either a panacea or a magic bullet: inference is a tool that allows us to be systematic in how we construct, debug, and improve the quality of such systems.
