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06/15/2023
KoLA: Carefully Benchmarking World Knowledge of Large Language Models
The unprecedented performance of large language models (LLMs) necessitat...
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06/12/2023
The Devil is in the Details: On the Pitfalls of Event Extraction Evaluation
Event extraction (EE) is a crucial task aiming at extracting events from...
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05/28/2023
Emergent Modularity in Pre-trained Transformers
This work examines the presence of modularity in pre-trained Transformer...
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05/23/2023
Preserving Knowledge Invariance: Rethinking Robustness Evaluation of Open Information Extraction
The robustness to distribution changes ensures that NLP models can be su...
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04/27/2023
ChatLog: Recording and Analyzing ChatGPT Across Time
While there are abundant researches about evaluating ChatGPT on natural ...
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03/26/2023
GOAL: A Challenging Knowledge-grounded Video Captioning Benchmark for Real-time Soccer Commentary Generation
Despite the recent emergence of video captioning models, how to generate...
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02/19/2023
Human Emotion Knowledge Representation Emerges in Large Language Model and Supports Discrete Emotion Inference
How humans infer discrete emotions is a fundamental research question in...
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02/14/2023
READIN: A Chinese Multi-Task Benchmark with Realistic and Diverse Input Noises
For many real-world applications, the user-generated inputs usually cont...
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11/14/2022
Finding Skill Neurons in Pre-trained Transformer-based Language Models
Transformer-based pre-trained language models have demonstrated superior...
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11/14/2022
MAVEN-ERE: A Unified Large-scale Dataset for Event Coreference, Temporal, Causal, and Subevent Relation Extraction
The diverse relationships among real-world events, including coreference...
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03/16/2022
LEVEN: A Large-Scale Chinese Legal Event Detection Dataset
Recognizing facts is the most fundamental step in making judgments, henc...
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12/24/2021
Doppler velocity-based algorithm for Clustering and Velocity Estimation of moving objects
We propose a Doppler velocity-based cluster and velocity estimation algo...
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11/12/2021
On Transferability of Prompt Tuning for Natural Language Understanding
Prompt tuning (PT) is a promising parameter-efficient method to utilize ...
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10/15/2021
Exploring Low-dimensional Intrinsic Task Subspace via Prompt Tuning
How can pre-trained language models (PLMs) learn universal representatio...
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06/01/2021
SHUOWEN-JIEZI: Linguistically Informed Tokenizers For Chinese Language Model Pretraining
Conventional tokenization methods for Chinese pretrained language models...
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05/30/2021
CLEVE: Contrastive Pre-training for Event Extraction
Event extraction (EE) has considerably benefited from pre-trained langua...
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12/01/2020
CPM: A Large-scale Generative Chinese Pre-trained Language Model
Pre-trained Language Models (PLMs) have proven to be beneficial for vari...
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04/28/2020
MAVEN: A Massive General Domain Event Detection Dataset
Event detection (ED), which identifies event trigger words and classifie...
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04/21/2020
Train No Evil: Selective Masking for Task-guided Pre-training
Recently, pre-trained language models mostly follow the pre-training-the...
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11/13/2019
KEPLER: A Unified Model for Knowledge Embedding and Pre-trained Language Representation
Pre-trained language representation models (PLMs) learn effective langua...
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11/05/2019