Grounding large language models (LLMs) connects their responses to trusted, verifiable sources, reducing the risk of false or misleading outputs. By integrating methods like retrieval-augmented ...

Yann LeCun’s argues that there are limitations of chain-of-thought (CoT) prompting and large language model (LLM) reasoning. LeCun argues that these fundamental limitations will require an entirely ...

Hallucinations, or factually inaccurate responses, continue to plague large language models (LLMs). Models falter particularly when they are given more complex tasks and when users are looking for ...

While Large Language Models (LLMs) like LLama 2 have shown remarkable prowess in understanding and generating text, they have a critical limitation: They can only answer questions based on single ...

New tools for filtering malicious prompts, detecting ungrounded outputs, and evaluating the safety of models will make generative AI safer to use. Both extremely promising and extremely risky, ...

AWS researchers have published a paper that pitches a proprietary LLM-based debugger, dubbed Panda, against OpenAI’s GPT-4. AWS researchers are working on developing a large language model-based ...