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This AI Paper Proposes Infini-Gram: A Groundbreaking Approach to Scale and Enhance N-Gram Models Beyond Traditional Limits

by | Feb 12, 2024 | Uncategorized

Pretrained on trillion-token corpora, large neural language models (LLMs) have achieved remarkable performance strides (Touvron et al., 2023a; Geng & Liu, 2023). However, the scalability benefits of such data for traditional n-gram language models (LMs) still need...

Outsmarting Uncertainty: How ‘K-Level Reasoning’ from Microsoft Research is Setting New Standards for LLMs

by | Feb 12, 2024 | Uncategorized

Delving into the intricacies of artificial intelligence, particularly within the dynamic reasoning domain, uncovers the pivotal role of Large Language Models (LLMs) in navigating environments that are not just complex but ever-changing. While effective in predictable...

Outsmarting Uncertainty: How ‘K-Level Reasoning’ from Microsoft Research is Setting New Standards for LLMs

by | Feb 12, 2024 | Uncategorized

Delving into the intricacies of artificial intelligence, particularly within the dynamic reasoning domain, uncovers the pivotal role of Large Language Models (LLMs) in navigating environments that are not just complex but ever-changing. While effective in predictable...

LLMWare Launches SLIMs: Small Specialized Function-Calling Models for Multi-Step Automation

by | Feb 12, 2024 | Uncategorized

As enterprises look to deploy LLMs in more complex production use cases beyond simple knowledge assistants, there is a growing recognition of three interconnected needs: Agents – complex workflows involve multiple steps and require the orchestration of multiple LLM...

Nomic AI Introduces Nomic Embed: Text Embedding Model with an 8192 Context-Length that Outperforms OpenAI Ada-002 and Text-Embedding-3-Small on both Short and Long Context Tasks

by | Feb 12, 2024 | Uncategorized

Nomic AI released an embedding model with a multi-stage training pipeline, Nomic Embed, an open-source, auditable, and high-performing text embedding model. It also has an extended context length supporting tasks such as retrieval-augmented-generation (RAG) and...

Can Large Language Models be Trusted for Evaluation? Meet SCALEEVAL: An Agent-Debate-Assisted Meta-Evaluation Framework that Leverages the Capabilities of Multiple Communicative LLM Agents

by | Feb 12, 2024 | Uncategorized

Despite the utility of large language models (LLMs) across various tasks and scenarios, researchers need help to evaluate LLMs properly in different situations. They use LLMs to check their responses, but a solution must be found. This method is limited because there...

This AI Paper Proposes Infini-Gram: A Groundbreaking Approach to Scale and Enhance N-Gram Models Beyond Traditional Limits

Outsmarting Uncertainty: How ‘K-Level Reasoning’ from Microsoft Research is Setting New Standards for LLMs

Outsmarting Uncertainty: How ‘K-Level Reasoning’ from Microsoft Research is Setting New Standards for LLMs

LLMWare Launches SLIMs: Small Specialized Function-Calling Models for Multi-Step Automation

Nomic AI Introduces Nomic Embed: Text Embedding Model with an 8192 Context-Length that Outperforms OpenAI Ada-002 and Text-Embedding-3-Small on both Short and Long Context Tasks

Can Large Language Models be Trusted for Evaluation? Meet SCALEEVAL: An Agent-Debate-Assisted Meta-Evaluation Framework that Leverages the Capabilities of Multiple Communicative LLM Agents

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