OpenGPT-X Team Publishes European LLM Leaderboard: Promoting the Way for Advanced Multilingual Language Model Development and Evaluation
The release of the European LLM Leaderboard by the OpenGPT-X team presents a great milestone in developing and evaluating multilingual language models. The project, supported by TU Dresden and a…
Can We Teach Transformers Causal Reasoning? This AI Paper Introduces Axiomatic Training: A Principle-Based Approach for Enhanced Causal Reasoning in AI Models
Artificial intelligence (AI) has transformed traditional research, propelling it to unprecedented heights. However, it has a ways to go regarding other spheres of its application. A critical issue in AI…
ETH Zurich Researchers Introduced EventChat: A CRS Using ChatGPT as Its Core Language Model Enhancing Small and Medium Enterprises with Advanced Conversational Recommender Systems
Conversational Recommender Systems (CRS) are revolutionizing how users make decisions by offering personalized suggestions through interactive dialogue interfaces. Unlike traditional systems that present predetermined options, CRS allows users to dynamically…
RoboMorph: Evolving Robot Design with Large Language Models and Evolutionary Machine Learning Algorithms for Enhanced Efficiency and Performance
The field of robotics is seeing transformative changes with the integration of generative methods like large language models (LLMs). These advancements enable the developing of sophisticated systems that autonomously navigate…
Samsung Researchers Introduce LoRA-Guard: A Parameter-Efficient Guardrail Adaptation Method that Relies on Knowledge Sharing between LLMs and Guardrail Models
Large Language Models (LLMs) have demonstrated remarkable proficiency in language generation tasks. However, their training process, which involves unsupervised learning from extensive datasets followed by supervised fine-tuning, presents significant challenges.…
Branch-and-Merge Method: Enhancing Language Adaptation in AI Models by Mitigating Catastrophic Forgetting and Ensuring Retention of Base Language Capabilities while Learning New Languages
Language model adaptation is a crucial area in artificial intelligence, focusing on enhancing large pre-trained language models to work effectively across various languages. This research is vital for enabling these…
Arena Learning: Transforming Post-Training of Large Language Models with AI-Powered Simulated Battles for Enhanced Efficiency and Performance in Natural Language Processing
Large language models (LLMs) have shown exceptional capabilities in understanding and generating human language, making substantial contributions to applications such as conversational AI. Chatbots powered by LLMs can engage in…
Metron: A Holistic AI Framework for Evaluating User-Facing Performance in LLM Inference Systems
Evaluating the performance of large language model (LLM) inference systems using conventional metrics presents significant challenges. Metrics such as Time To First Token (TTFT) and Time Between Tokens (TBT) do…
Optimizing Large Language Models (LLMs) on CPUs: Techniques for Enhanced Inference and Efficiency
Large Language Models (LLMs) built on the Transformer architecture have recently attained important technological milestones. The remarkable skills of these models in comprehending and producing writing that resembles that of…
Meet Reworkd: An AI Startup that Automates End-to-end Data Extraction
Collecting, monitoring, and maintaining a web data pipeline can be daunting and time-consuming when dealing with large amounts of data. Traditional approaches’ struggles can compromise data quality and availability with…