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Found 11 papers, 1 papers with code
Neural Anaphora Resolution in Dialogue
We describe the systems that we developed for the three tracks of the CODI-CRAC 2021 shared task, namely entity coreference resolution, bridging resolution, and discourse deixis resolution.
The CODI-CRAC 2021 Shared Task on Anaphora, Bridging, and Discourse Deixis Resolution in Dialogue: A Cross-Team Analysis
The CODI-CRAC 2021 shared task is the first shared task that focuses exclusively on anaphora resolution in dialogue and provides three tracks, namely entity coreference resolution, bridging resolution, and discourse deixis resolution.
Summarizing Dialogues with Negative Cues
In this work, rather than directly forcing a summarization system to merely pay more attention to the salient pieces, we propose to explicitly have the model perceive the redundant parts of an input dialogue history during the training phase.
Neural Anaphora Resolution in Dialogue Revisited
We present the systems that we developed for all three tracks of the CODI-CRAC 2022 shared task, namely the anaphora resolution track, the bridging resolution track, and the discourse deixis resolution track.
A Depression Detection Method Based on Multi-Modal Feature Fusion Using Cross-Attention
Depression, a prevalent and serious mental health issue, affects approximately 3. 8\% of the global population.
Multimodal Propaganda Processing
Propaganda campaigns have long been used to influence public opinion via disseminating biased and/or misleading information.
End-to-End Neural Discourse Deixis Resolution in Dialogue
We adapt Lee et al.'s (2018) span-based entity coreference model to the task of end-to-end discourse deixis resolution in dialogue, specifically by proposing extensions to their model that exploit task-specific characteristics.
Segmenting Epipolar Line
Identifying feature correspondence between two images is a fundamental procedure in three-dimensional computer vision.
Cross-modal Coherence Modeling for Caption Generation
We use coherence relations inspired by computational models of discourse to study the information needs and goals of image captioning.
Clue: Cross-modal Coherence Modeling for Caption Generation
We use coherence relations inspired by computational models of discourse to study the information needs and goals of image captioning.
SDOD:Real-time Segmenting and Detecting 3D Object by Depth
We produce an instance mask by assigning pixels which have the same depth categories to each instance.
