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[HTML][HTML] Exploring the frontiers of deep learning and natural language processing: A comprehensive overview of key challenges and emerging trends
In the recent past, more than 5 years or so, Deep Learning (DL) especially the large
language models (LLMs) has generated extensive studies out of a distinctly average …
language models (LLMs) has generated extensive studies out of a distinctly average …
[HTML][HTML] Advancements in complex knowledge graph question answering: a survey
Y Song, W Li, G Dai, X Shang - Electronics, 2023 - mdpi.com
Complex Question Answering over Knowledge Graph (C-KGQA) seeks to solve complex
questions using knowledge graphs. Currently, KGQA systems achieve great success in …
questions using knowledge graphs. Currently, KGQA systems achieve great success in …
FC-KBQA: A fine-to-coarse composition framework for knowledge base question answering
The generalization problem on KBQA has drawn considerable attention. Existing research
suffers from the generalization issue brought by the entanglement in the coarse-grained …
suffers from the generalization issue brought by the entanglement in the coarse-grained …
Glm-dialog: Noise-tolerant pre-training for knowledge-grounded dialogue generation
We present GLM-Dialog, a large-scale language model (LLM) with 10B parameters capable
of knowledge-grounded conversation in Chinese using a search engine to access the …
of knowledge-grounded conversation in Chinese using a search engine to access the …
Aligning language models to explicitly handle ambiguity
In interactions between users and language model agents, user utterances frequently
exhibit ellipsis (omission of words or phrases) or imprecision (lack of exactness) to prioritize …
exhibit ellipsis (omission of words or phrases) or imprecision (lack of exactness) to prioritize …
Extractive question answering over ancient scriptures texts using generative AI and natural language processing techniques
Generative AI (GenAI) and Natural Language Processing (NLP) are transforming the
landscape of question-answering systems, shifting from traditional methods to more …
landscape of question-answering systems, shifting from traditional methods to more …
Dynamic multi teacher knowledge distillation for semantic parsing in KBQA
Abstract Knowledge base question answering (KBQA) is an important task of extracting
answers from a knowledge base by analyzing natural language questions. Semantic …
answers from a knowledge base by analyzing natural language questions. Semantic …
When to Speak, When to Abstain: Contrastive Decoding with Abstention
Large Language Models (LLMs) demonstrate exceptional performance across diverse tasks
by leveraging both pre-trained knowledge (ie, parametric knowledge) and external …
by leveraging both pre-trained knowledge (ie, parametric knowledge) and external …
[HTML][HTML] SecureTLM: Private inference for transformer-based large model with MPC
Y Chen, X Meng, Z Shi, Z Ning, J Lin - Information Sciences, 2024 - Elsevier
Abstract Transformer-based Large Models (TLM), such as generative pre-trained models
(GPT), have become increasingly popular for practical applications through Deep Learning …
(GPT), have become increasingly popular for practical applications through Deep Learning …
Hybrid-SQuAD: Hybrid Scholarly Question Answering Dataset
Existing Scholarly Question Answering (QA) methods typically target homogeneous data
sources, relying solely on either text or Knowledge Graphs (KGs). However, scholarly …
sources, relying solely on either text or Knowledge Graphs (KGs). However, scholarly …