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Found 32 papers, 7 papers with code
Unsupervised Domain Adaptation Method with Semantic-Structural Alignment for Dependency Parsing
Unsupervised cross-domain dependency parsing is to accomplish domain adaptation for dependency parsing without using labeled data in target domain.
Simple Tagging System with RoBERTa for Ancient Chinese
This paper describes the system submitted for the EvaHan 2022 Shared Task on word segmentation and part-of-speech tagging for Ancient Chinese.
Multi-Turn Target-Guided Topic Prediction with Monte Carlo Tree Search
In this paper, we formulate the target-guided conversation as a problem of multi-turn topic prediction and model it under the framework of Markov decision process (MDP).
ChatGPT is a Potential Zero-Shot Dependency Parser
Pre-trained language models have been widely used in dependency parsing task and have achieved significant improvements in parser performance.
Type-aware Decoding via Explicitly Aggregating Event Information for Document-level Event Extraction
Although previous methods attempt to address these challenges, they overlook the interference of event-unrelated sentences during event detection and neglect the mutual interference of different event roles during argument extraction.
DemoSG: Demonstration-enhanced Schema-guided Generation for Low-resource Event Extraction
Most current Event Extraction (EE) methods focus on the high-resource scenario, which requires a large amount of annotated data and can hardly be applied to low-resource domains.
L-CoIns: Language-Based Colorization With Instance Awareness
Language-based colorization produces plausible colors consistent with the language description provided by the user.
Complementary Intrinsics From Neural Radiance Fields and CNNs for Outdoor Scene Relighting
Relighting an outdoor scene is challenging due to the diverse illuminations and salient cast shadows.
Affective Image Filter: Reflecting Emotions from Text to Images
In this work, we propose Affective Image Filter (AIF), a novel model that is able to understand the visually-abstract emotions from the text and reflect them to visually-concrete images with appropriate colors and textures.
CT2: Colorization Transformer via Color Tokens
Automatic image colorization is an ill-posed problem with multi-modal uncertainty, and there remains two main challenges with previous methods: incorrect semantic colors and under-saturation.
AdsCVLR: Commercial Visual-Linguistic Representation Modeling in Sponsored Search
Sponsored search advertisements (ads) appear next to search results when consumers look for products and services on search engines.
Ranked #3 on
Image-text matching
on CommercialAdsDataset
Schema-Free Dependency Parsing via Sequence Generation
To remedy these drawbacks, we propose to achieve universal and schema-free Dependency Parsing (DP) via Sequence Generation (SG) DPSG by utilizing only the pre-trained language model (PLM) without any auxiliary structures or parsing algorithms.
UniCoRN: A Unified Conditional Image Repainting Network
Conditional image repainting (CIR) is an advanced image editing task, which requires the model to generate visual content in user-specified regions conditioned on multiple cross-modality constraints, and composite the visual content with the provided background seamlessly.
A Joint Model for Dropped Pronoun Recovery and Conversational Discourse Parsing in Chinese Conversational Speech
A second (multi-relational) GCN is then applied to the utterance states to produce a discourse relation-augmented representation for the utterances, which are then fused together with token states in each utterance as input to a dropped pronoun recovery layer.
Ranked #5 on
Discourse Parsing
on STAC
DeRenderNet: Intrinsic Image Decomposition of Urban Scenes with Shape-(In)dependent Shading Rendering
We propose DeRenderNet, a deep neural network to decompose the albedo and latent lighting, and render shape-(in)dependent shadings, given a single image of an outdoor urban scene, trained in a self-supervised manner.
Spatially-Varying Outdoor Lighting Estimation from Intrinsics
We train a deep neural network to regress intrinsic cues with physically-based constraints and use them to conduct global and local lightings estimation.
Transformer-GCRF: Recovering Chinese Dropped Pronouns with General Conditional Random Fields
Exploratory analysis also demonstrates that the GCRF did help to capture the dependencies between pronouns in neighboring utterances, thus contributes to the performance improvements.
ST-MNIST -- The Spiking Tactile MNIST Neuromorphic Dataset
We anticipate that our ST-MNIST dataset will be of interest and useful to the neuromorphic and robotics research communities.
Reflection Separation using a Pair of Unpolarized and Polarized Images
When we take photos through glass windows or doors, the transmitted background scene is often blended with undesirable reflection.
A Prism Module for Semantic Disentanglement in Name Entity Recognition
To solve this problem, we propose a prism module to disentangle the semantic aspects of words and reduce noise at the input layer of a model.
Ranked #52 on
Named Entity Recognition (NER)
on CoNLL 2003 (English)
Dynamic PET cardiac and parametric image reconstruction: a fixed-point proximity gradient approach using patch-based DCT and tensor SVD regularization
For the cardiac/lung phantom, an additional cardiac gated 2D-OSEM set was reconstructed.
Recovering Dropped Pronouns in Chinese Conversations via Modeling Their Referents
Pronouns are often dropped in Chinese sentences, and this happens more frequently in conversational genres as their referents can be easily understood from context.
Cyclone intensity estimate with context-aware cyclegan
Deep learning approaches to cyclone intensity estimationhave recently shown promising results.
From Random to Supervised: A Novel Dropout Mechanism Integrated with Global Information
Dropout is used to avoid overfitting by randomly dropping units from the neural networks during training.
Contextualized Character Representation for Chinese Grammatical Error Diagnosis
Nowadays, more and more people are learning Chinese as their second language.
Guiding Generation for Abstractive Text Summarization Based on Key Information Guide Network
Then, we introduce a Key Information Guide Network (KIGN), which encodes the keywords to the key information representation, to guide the process of generation.
Ranked #10 on
Text Summarization
on CNN / Daily Mail (Anonymized)
N-gram Model for Chinese Grammatical Error Diagnosis
Detection and correction of Chinese grammatical errors have been two of major challenges for Chinese automatic grammatical error diagnosis. This paper presents an N-gram model for automatic detection and correction of Chinese grammatical errors in NLPTEA 2017 task.
Neural Regularized Domain Adaptation for Chinese Word Segmentation
For Chinese word segmentation, the large-scale annotated corpora mainly focus on newswire and only a handful of annotated data is available in other domains such as patents and literature.
Towards Accurate Word Segmentation for Chinese Patents
A patent is a property right for an invention granted by the government to the inventor.
Twisted supergravity and its quantization
For type IIB, the results of arXiv:1505. 6703 show that our candidate twisted supergravity theory admits a unique quantization in perturbation theory.
High Energy Physics - Theory Algebraic Geometry
