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Found 10 papers, 2 papers with code
Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone
We introduce phi-3-mini, a 3. 8 billion parameter language model trained on 3. 3 trillion tokens, whose overall performance, as measured by both academic benchmarks and internal testing, rivals that of models such as Mixtral 8x7B and GPT-3. 5 (e. g., phi-3-mini achieves 69% on MMLU and 8. 38 on MT-bench), despite being small enough to be deployed on a phone.
GenSERP: Large Language Models for Whole Page Presentation
(2) An answer generation phase where the LLM populates the layouts with the retrieved content.
Model Tells You What to Discard: Adaptive KV Cache Compression for LLMs
In this study, we introduce adaptive KV cache compression, a plug-and-play method that reduces the memory footprint of generative inference for Large Language Models (LLMs).
A Neural Span-Based Continual Named Entity Recognition Model
Named Entity Recognition (NER) models capable of Continual Learning (CL) are realistically valuable in areas where entity types continuously increase (e. g., personal assistants).
Continual Named Entity Recognition
Knowledge Distillation
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Towards Disentangling Relevance and Bias in Unbiased Learning to Rank
We give both theoretical analysis and empirical results to show the negative effects on relevance tower due to such a correlation.
Unifying Model Explainability and Robustness for Joint Text Classification and Rationale Extraction
Recent works have shown explainability and robustness are two crucial ingredients of trustworthy and reliable text classification.
No Feature Is An Island: Adaptive Collaborations Between Features Improve Adversarial Robustness
To classify images, neural networks extract features from raw inputs and then sum them up with fixed weights via the fully connected layer.
Cooperative Reasoning on Knowledge Graph and Corpus: A Multi-agentReinforcement Learning Approach
We model the question answering on KG as a cooperative task between two agents, a knowledge graph reasoning agent and an information extraction agent.
Macross: Urban Dynamics Modeling based on Metapath Guided Cross-Modal Embedding
As the ongoing rapid urbanization takes place with an ever-increasing speed, fully modeling urban dynamics becomes more and more challenging, but also a necessity for socioeconomic development.
Learning to Order Sub-questions for Complex Question Answering
Answering complex questions involving multiple entities and relations is a challenging task.
