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Found 11 papers, 1 papers with code
Factorized Learning Assisted with Large Language Model for Gloss-free Sign Language Translation
Although some approaches work towards gloss-free SLT through jointly training the visual encoder and translation network, these efforts still suffer from poor performance and inefficient use of the powerful Large Language Model (LLM).
Ranked #1 on
Gloss-free Sign Language Translation
on CSL-Daily
R2-Talker: Realistic Real-Time Talking Head Synthesis with Hash Grid Landmarks Encoding and Progressive Multilayer Conditioning
This approach losslessly encodes landmark structures as conditional features, decoupling input diversity, and conditional spaces by mapping arbitrary landmarks to a unified feature space.
PMMTalk: Speech-Driven 3D Facial Animation from Complementary Pseudo Multi-modal Features
The framework entails three modules: PMMTalk encoder, cross-modal alignment module, and PMMTalk decoder.
Conversational Speech Recognition by Learning Audio-textual Cross-modal Contextual Representation
By introducing both cross-modal and conversational representations into the decoder, our model retains context over longer sentences without information loss, achieving relative accuracy improvements of 8. 8% and 23% on Mandarin conversation datasets HKUST and MagicData-RAMC, respectively, compared to the standard Conformer model.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
Modeling Price Elasticity for Occupancy Prediction in Hotel Dynamic Pricing
Demand estimation plays an important role in dynamic pricing where the optimal price can be obtained via maximizing the revenue based on the demand curve.
SAR-Net: A Scenario-Aware Ranking Network for Personalized Fair Recommendation in Hundreds of Travel Scenarios
In this paper, we propose a novel Scenario-Aware Ranking Network (SAR-Net) to address these issues.
Sharp Multiple Instance Learning for DeepFake Video Detection
A sharp MIL (S-MIL) is proposed which builds direct mapping from instance embeddings to bag prediction, rather than from instance embeddings to instance prediction and then to bag prediction in traditional MIL.
SpanMlt: A Span-based Multi-Task Learning Framework for Pair-wise Aspect and Opinion Terms Extraction
To this end, this paper proposes an end-to-end method to solve the task of Pair-wise Aspect and Opinion Terms Extraction (PAOTE).
Aspect-Based Sentiment Analysis
Aspect-Based Sentiment Analysis (ABSA)
+3
Field-weighted Factorization Machines for Click-Through Rate Prediction in Display Advertising
The data involved in CTR prediction are typically multi-field categorical data, i. e., every feature is categorical and belongs to one and only one field.
Lift-Based Bidding in Ad Selection
In this paper, we propose a new bidding strategy and prove that if the bid price is decided based on the performance lift rather than absolute performance value, advertisers can actually gain more action events.
Smart Pacing for Effective Online Ad Campaign Optimization
In this paper, we propose a smart pacing approach in which the delivery pace of each campaign is learned from both offline and online data to achieve smooth delivery and optimal performance goals.
