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Found 17 papers, 5 papers with code
Gradient Deconfliction via Orthogonal Projections onto Subspaces For Multi-task Learning
Although multi-task learning (MTL) has been a preferred approach and successfully applied in many real-world scenarios, MTL models are not guaranteed to outperform single-task models on all tasks mainly due to the negative effects of conflicting gradients among the tasks.
UQABench: Evaluating User Embedding for Prompting LLMs in Personalized Question Answering
To address this concern, we propose \name, a benchmark designed to evaluate the effectiveness of user embeddings in prompting LLMs for personalization.
VALUE: Value-Aware Large Language Model for Query Rewriting via Weighted Trie in Sponsored Search
In the realm of sponsored search advertising, matching advertisements with the search intent of a user's query is crucial.
MIM: Multi-modal Content Interest Modeling Paradigm for User Behavior Modeling
Click-Through Rate (CTR) prediction is a crucial task in recommendation systems, online searches, and advertising platforms, where accurately capturing users' real interests in content is essential for performance.
Explainable LLM-driven Multi-dimensional Distillation for E-Commerce Relevance Learning
Effective query-item relevance modeling is pivotal for enhancing user experience and safeguarding user satisfaction in e-commerce search systems.
Puzzle Pieces Picker: Deciphering Ancient Chinese Characters with Radical Reconstruction
Oracle Bone Inscriptions is one of the oldest existing forms of writing in the world.
An open dataset for oracle bone script recognition and decipherment
Oracle bone script, one of the earliest known forms of ancient Chinese writing, presents invaluable research materials for scholars studying the humanities and geography of the Shang Dynasty, dating back 3, 000 years.
An open dataset for the evolution of oracle bone characters: EVOBC
We conducted validation and simulated deciphering on the constructed dataset, and the results demonstrate its high efficacy in aiding the study of oracle bone script.
GBA: A Tuning-free Approach to Switch between Synchronous and Asynchronous Training for Recommendation Model
High-concurrency asynchronous training upon parameter server (PS) architecture and high-performance synchronous training upon all-reduce (AR) architecture are the most commonly deployed distributed training modes for recommendation models.
APG: Adaptive Parameter Generation Network for Click-Through Rate Prediction
In many web applications, deep learning-based CTR prediction models (deep CTR models for short) are widely adopted.
Asymptotically Unbiased Estimation for Delayed Feedback Modeling via Label Correction
Moreover, to estimate CVR upon the freshly observed but biased distribution with fake negatives, the importance sampling is widely used to reduce the distribution bias.
Binary Code based Hash Embedding for Web-scale Applications
In these applications, embedding learning of categorical features is crucial to the success of deep learning models.
Learning Effective and Efficient Embedding via an Adaptively-Masked Twins-based Layer
Each feature value is mapped to an embedding vector via an embedding learning process.
Explicit Semantic Cross Feature Learning via Pre-trained Graph Neural Networks for CTR Prediction
Most of the existing methods adopt a DNN-based model to capture the cross features in an implicit manner.
Towards a Better Tradeoff between Effectiveness and Efficiency in Pre-Ranking: A Learnable Feature Selection based Approach
In real-world search, recommendation, and advertising systems, the multi-stage ranking architecture is commonly adopted.
Graph Intention Network for Click-through Rate Prediction in Sponsored Search
Moreover, it is difficult for user to jump out of their specific historical behaviors for possible interest exploration, namely weak generalization problem.
Landau Quantization and Highly Mobile Fermions in an Insulator
Using a detection scheme that avoids edge contributions, we uncover strikingly large quantum oscillations in the monolayer insulator's magnetoresistance, with an onset field as small as ~ 0. 5 tesla.
Mesoscale and Nanoscale Physics Materials Science Strongly Correlated Electrons
