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Found 11 papers, 2 papers with code
RESTRAIN: Reinforcement Learning-Based Secure Framework for Trigger-Action IoT Environment
The state-of-the-art online defense mechanisms offer real-time defense, but extensive reliability on the inference of attack impacts on the IoT network limits the generalization capability of these approaches.
Hunyuan-Large: An Open-Source MoE Model with 52 Billion Activated Parameters by Tencent
In this paper, we introduce Hunyuan-Large, which is currently the largest open-source Transformer-based mixture of experts model, with a total of 389 billion parameters and 52 billion activation parameters, capable of handling up to 256K tokens.
UniRetriever: Multi-task Candidates Selection for Various Context-Adaptive Conversational Retrieval
Conversational retrieval refers to an information retrieval system that operates in an iterative and interactive manner, requiring the retrieval of various external resources, such as persona, knowledge, and even response, to effectively engage with the user and successfully complete the dialogue.
Large Language Models as Source Planner for Personalized Knowledge-grounded Dialogue
Open-domain dialogue system usually requires different sources of knowledge to generate more informative and evidential responses.
Improving Factual Consistency for Knowledge-Grounded Dialogue Systems via Knowledge Enhancement and Alignment
Inspired by previous work which identified that feed-forward networks (FFNs) within Transformers are responsible for factual knowledge expressions, we investigate two methods to efficiently improve the factual expression capability {of FFNs} by knowledge enhancement and alignment respectively.
SELF: Self-Evolution with Language Feedback
SELF initiates with a meta-skill learning process that equips the LLMs with capabilities for self-feedback and self-refinement.
PanGu-Σ: Towards Trillion Parameter Language Model with Sparse Heterogeneous Computing
In this work, we develop a system that trained a trillion-parameter language model on a cluster of Ascend 910 AI processors and MindSpore framework, and present the language model with 1. 085T parameters named PanGu-{\Sigma}.
Towards Diverse, Relevant and Coherent Open-Domain Dialogue Generation via Hybrid Latent Variables
Specifically, HLV constrains the global semantics of responses through discrete latent variables and enriches responses with continuous latent variables.
Modeling Complex Dialogue Mappings via Sentence Semantic Segmentation Guided Conditional Variational Auto-Encoder
Complex dialogue mappings (CDM), including one-to-many and many-to-one mappings, tend to make dialogue models generate incoherent or dull responses, and modeling these mappings remains a huge challenge for neural dialogue systems.
Answer-guided and Semantic Coherent Question Generation in Open-domain Conversation
We observe that the answer has strong semantic coherence to its question and post, which can be used to guide question generation.
Personalized Microblog Sentiment Classification via Adversarial Cross-lingual Multi-task Learning
Then the attention-based CNN model is incorporated into a novel adversarial cross-lingual learning framework, in which with the help of user properties as bridge between languages, we can extract the language-specific features and language-independent features to enrich the user post representation so as to alleviate the data insufficiency problem.
