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Found 18 papers, 3 papers with code
Decoding, Fast and Slow: A Case Study on Balancing Trade-Offs in Incremental, Character-level Pragmatic Reasoning
Recent work has adopted models of pragmatic reasoning for the generation of informative language in, e. g., image captioning.
Diversity as a By-Product: Goal-oriented Language Generation Leads to Linguistic Variation
The ability for variation in language use is necessary for speakers to achieve their conversational goals, for instance when referring to objects in visual environments.
Depth Matters: Exploring Deep Interactions of RGB-D for Semantic Segmentation in Traffic Scenes
RGB-D has gradually become a crucial data source for understanding complex scenes in assisted driving.
Seed-ASR: Understanding Diverse Speech and Contexts with LLM-based Speech Recognition
Modern automatic speech recognition (ASR) model is required to accurately transcribe diverse speech signals (from different domains, languages, accents, etc) given the specific contextual information in various application scenarios.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
Comparative Analysis of Advanced Feature Matching Algorithms in Challenging High Spatial Resolution Optical Satellite Stereo Scenarios
Feature matching determines the orientation accuracy for the High Spatial Resolution (HSR) optical satellite stereos, subsequently impacting several significant applications such as 3D reconstruction and change detection.
Adaptive loose optimization for robust question answering
Question answering methods are well-known for leveraging data bias, such as the language prior in visual question answering and the position bias in machine reading comprehension (extractive question answering).
Extractive Question-Answering
Machine Reading Comprehension
+2
TCBERT: A Technical Report for Chinese Topic Classification BERT
Bidirectional Encoder Representations from Transformers or BERT~\cite{devlin-etal-2019-bert} has been one of the base models for various NLP tasks due to its remarkable performance.
Fengshenbang 1.0: Being the Foundation of Chinese Cognitive Intelligence
We hope that this project will be the foundation of Chinese cognitive intelligence.
Coreference Augmentation for Multi-Domain Task-Oriented Dialogue State Tracking
Dialogue State Tracking (DST), which is the process of inferring user goals by estimating belief states given the dialogue history, plays a critical role in task-oriented dialogue systems.
Enabling Robots to Draw and Tell: Towards Visually Grounded Multimodal Description Generation
Socially competent robots should be equipped with the ability to perceive the world that surrounds them and communicate about it in a human-like manner.
MultiWOZ 2.3: A multi-domain task-oriented dialogue dataset enhanced with annotation corrections and co-reference annotation
In this paper, we introduce MultiWOZ 2. 3, in which we differentiate incorrect annotations in dialogue acts from dialogue states, identifying a lack of co-reference when publishing the updated dataset.
Mandarinograd: A Chinese Collection of Winograd Schemas
This article introduces Mandarinograd, a corpus of Winograd Schemas in Mandarin Chinese.
Sketch Me if You Can: Towards Generating Detailed Descriptions of Object Shape by Grounding in Images and Drawings
A lot of recent work in Language {\&} Vision has looked at generating descriptions or referring expressions for objects in scenes of real-world images, though focusing mostly on relatively simple language like object names, color and location attributes (e. g., brown chair on the left).
Draw and Tell: Multimodal Descriptions Outperform Verbal- or Sketch-Only Descriptions in an Image Retrieval Task
While language conveys meaning largely symbolically, actual communication acts typically contain iconic elements as well: People gesture while they speak, or may even draw sketches while explaining something.
Natural Language Informs the Interpretation of Iconic Gestures: A Computational Approach
When giving descriptions, speakers often signify object shape or size with hand gestures.
Grounding Language by Continuous Observation of Instruction Following
Grounded semantics is typically learnt from utterance-level meaning representations (e. g., successful database retrievals, denoted objects in images, moves in a game).
Usability Investigation on the Localization of Text CAPTCHAs: Take Chinese Characters as a Case Study
Moreover, those design practices were also summarized as a general procedure which is expected to be applicable for the design of CAPTCHAs based on other languages.
Human-Computer Interaction
