COMPUTERCOMBusiness Directories,Company Directories

Company Name: Corporate Name:	COMPUTERCOM
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Company Address:	58 Manitoba Dr,CLARENVILLE,NL,Canada
ZIP Code: Postal Code:	A0E1J0
Telephone Number:	7094664450
Fax Number:	7094664451
Website:
Email:
USA SIC Code(Standard Industrial Classification Code):	573407
USA SIC Description:	Computer & Equipment Dealers
Number of Employees:	1 to 4
Sales Amount:	$1 to 2.5 million
Credit History: Credit Report:	Good
Contact Person:	Walter Blackmore
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Infinite Retrieval: Attention Enhanced LLMs in Long-Context Processing
Drawing on the above insights, we propose a novel method InfiniRetri that leverages the LLMs's own attention information to enable accurate retrieval across inputs of infinitely length
InfiniRetri README. md at main · MrYxJ InfiniRetri · GitHub
Implementation of currently Submitting Paper: " Infinite Retrieval: Attention Enhanced LLMs in Long Context Processing ", which can apply any Transformer-based LLMs (Large Language Moidels) to handle long-context without training
Infinite Retrieval: Attention Enhanced LLMs in Long-Context Processing
This survey provides an inclusive review of the recent techniques and methods devised to extend the sequence length in LLMs, thereby enhancing their capacity for long-context understanding
Overview: InfiniRetri: Enhancing LLMs for Infinite-Length Context via . . .
This paper introduces InfiniRetri, a novel and training-free method that leverages the inherent attention mechanisms of Large Language Models (LLMs) to achieve accurate retrieval across inputs of theoretically infinite length
Summary: Infinite Retrieval: Attention Enhanced LLMs in Long-Context . . .
Proposes InfiniRetri, a training-free framework that equips any Transformer LLM with “infinite” context length by treating the model’s own attention scores as a retrieval signal
Infinite Retrieval: Attention Enhanced LLMs in Long-Context Processing
In this paper, the authors propose InfiniRetri, a novel method that leverages LLMs’ own attention mechanisms to enhance retrieval capabilities for inputs of virtually unlimited length
Infinite Retrieval: Attention Enhanced LLMs in Long-Context Processing
Overall, our work provides a novel and effective solution for long-text processing in LLMs, paving the way for future research on efficient retrieval and context extension
How a New AI Method is Revolutionizing Long Text Processing
Researchers at BNU have proposed a groundbreaking method called InfiniRetri that leverages the LLMs' own attention mechanism to achieve accurate information retrieval across inputs of virtually unlimited length
Infinite Retrieval
Implementation of currently Submitting Paper: " Infinite Retrieval: Attention Enhanced LLMs in Long Context Processing ", which can apply any Transformer-based LLMs (Large Language Moidels) to handle unlimited length texts without training
Infinite Retrieval: Attention Enhanced LLMs in Long-Context Processing
InfiniRetri, a novel method leveraging LLMs' attention information, enables accurate retrieval across infinitely long inputs and outperforms other methods on real-world benchmarks with minimal computational overhead