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06/06/2023
A Quantum Probability Driven Framework for Joint Multi-Modal Sarcasm, Sentiment and Emotion Analysis
Sarcasm, sentiment, and emotion are three typical kinds of spontaneous a...
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06/06/2023
A Survey of Quantum-Cognitively Inspired Sentiment Analysis Models
Quantum theory, originally proposed as a physical theory to describe the...
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05/21/2023
Task-agnostic Distillation of Encoder-Decoder Language Models
Finetuning pretrained language models (LMs) have enabled appealing perfo...
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05/20/2023
Lifting the Curse of Capacity Gap in Distilling Language Models
Pretrained language models (LMs) have shown compelling performance on va...
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03/23/2023
Modular Retrieval for Generalization and Interpretation
New retrieval tasks have always been emerging, thus urging the developme...
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10/18/2022
DisCup: Discriminator Cooperative Unlikelihood Prompt-tuning for Controllable Text Generation
Prompt learning with immensely large Casual Language Models (CLMs) has b...
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10/10/2022
XPrompt: Exploring the Extreme of Prompt Tuning
Prompt tuning learns soft prompts to condition frozen Pre-trained Langua...
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10/08/2022
Sparse Teachers Can Be Dense with Knowledge
Recent advances in distilling pretrained language models have discovered...
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09/02/2022
Structural Bias for Aspect Sentiment Triplet Extraction
Structural bias has recently been exploited for aspect sentiment triplet...
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07/20/2022
Doge Tickets: Uncovering Domain-general Language Models by Playing Lottery Tickets
Over-parameterized models, typically pre-trained language models (LMs), ...
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07/17/2022
A Multibias-mitigated and Sentiment Knowledge Enriched Transformer for Debiasing in Multimodal Conversational Emotion Recognition
Multimodal emotion recognition in conversations (mERC) is an active rese...
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07/17/2022
Aspect-specific Context Modeling for Aspect-based Sentiment Analysis
Aspect-based sentiment analysis (ABSA) aims at predicting sentiment pola...
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05/29/2022
AutoDisc: Automatic Distillation Schedule for Large Language Model Compression
Driven by the teacher-student paradigm, knowledge distillation is one of...
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05/11/2022
Making Pre-trained Language Models Good Long-tailed Learners
Prompt-tuning has shown appealing performance in few-shot classification...
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04/27/2022
Adaptable Text Matching via Meta-Weight Regulator
Neural text matching models have been used in a range of applications su...
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05/29/2021
Exploiting Position Bias for Robust Aspect Sentiment Classification
Aspect sentiment classification (ASC) aims at determining sentiments exp...
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01/12/2021
Quantum Cognitively Motivated Decision Fusion for Video Sentiment Analysis
Video sentiment analysis as a decision-making process is inherently comp...
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10/04/2020
A Multi-task Learning Framework for Opinion Triplet Extraction
The state-of-the-art Aspect-based Sentiment Analysis (ABSA) approaches a...
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09/19/2020
Redundancy of Hidden Layers in Deep Learning: An Information Perspective
Although the deep structure guarantees the powerful expressivity of deep...
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07/08/2020
A Survey of Quantum Theory Inspired Approaches to Information Retrieval
Since 2004, researchers have been using the mathematical framework of Qu...
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02/25/2020
End-to-end Emotion-Cause Pair Extraction via Learning to Link
Emotion-cause pair extraction (ECPE), as an emergent natural language pr...
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02/18/2020
Assessing the Memory Ability of Recurrent Neural Networks
It is known that Recurrent Neural Networks (RNNs) can remember, in their...
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01/20/2020
Quantum-like Structure in Multidimensional Relevance Judgements
A large number of studies in cognitive science have revealed that probab...
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09/23/2019
Syntax-Aware Aspect-Level Sentiment Classification with Proximity-Weighted Convolution Network
It has been widely accepted that Long Short-Term Memory (LSTM) network, ...
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09/08/2019
Aspect-based Sentiment Classification with Aspect-specific Graph Convolutional Networks
Due to their inherent capability in semantic alignment of aspects and th...
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07/25/2019
Modelling Dynamic Interactions between Relevance Dimensions
Relevance is an underlying concept in the field of Information Science a...
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07/12/2019
ScenarioSA: A Large Scale Conversational Database for Interactive Sentiment Analysis
Interactive sentiment analysis is an emerging, yet challenging, subtask ...
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06/24/2019
A Tensorized Transformer for Language Modeling
Latest development of neural models has connected the encoder and decode...
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03/08/2019
A Quantum Observation Scheme Can Universally Identify Causalities from Correlations
It has long been recognized as a difficult problem to determine whether ...
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02/26/2019
Semantic Hilbert Space for Text Representation Learning
Capturing the meaning of sentences has long been a challenging task. Cur...
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01/31/2019
A Generalized Language Model in Tensor Space
In the literature, tensors have been effectively used for capturing the ...
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11/30/2018
Structured Information Retrieval Strategies for Localising Software Changes
During software maintenance and evolution, developers need to deal with ...
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11/16/2018
Investigating Bell Inequalities for Multidimensional Relevance Judgments in Information Retrieval
Relevance judgment in Information Retrieval is influenced by multiple fa...
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10/26/2018
Investigating non-classical correlations between decision fused multi-modal documents
Correlation has been widely used to facilitate various information retri...
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08/28/2018
A Quantum Many-body Wave Function Inspired Language Modeling Approach
The recently proposed quantum language model (QLM) aimed at a principled...
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08/14/2018
Reconciling Irrational Human Behavior with AI based Decision Making: A Quantum Probabilistic Approach
There are many examples of human decision making which cannot be modeled...
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07/14/2018
Investigating Order Effects in Multidimensional Relevance Judgment using Query Logs
There is a growing body of research which has investigated relevance jud...
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05/29/2018
Quantum-inspired Complex Word Embedding
A challenging task for word embeddings is to capture the emergent meanin...
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05/06/2018
Modeling Multidimensional User Relevance in IR using Vector Spaces
It has been shown that relevance judgment of documents is influenced by ...
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12/12/2016
Search Personalization with Embeddings
Recent research has shown that the performance of search personalization...
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02/05/2015
A Confident Information First Principle for Parametric Reduction and Model Selection of Boltzmann Machines
Typical dimensionality reduction (DR) methods are often data-oriented, f...
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02/16/2013
Understanding Boltzmann Machine and Deep Learning via A Confident Information First Principle
Typical dimensionality reduction methods focus on directly reducing the ...
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04/07/2010