Scientific discoveries often hinge on synthesizing decades of research, a task that potentially
outstrips human information processing capacities. Large language models (LLMs) offer a …

Large language models (LLMs) fine-tuned with reinforcement learning from human
feedback (RLHF) have been used in some of the most widely deployed AI models to date …

Abstract Retrieval-Augmented Generation (RAG) has recently gained traction in natural
language processing. Numerous studies and real-world applications are leveraging its …

LLM watermarking has attracted attention as a promising way to detect AI-generated
content, with some works suggesting that current schemes may already be fit for …

We present MEGA-Bench, an evaluation suite that scales multimodal evaluation to over 500
real-world tasks, to address the highly heterogeneous daily use cases of end users. Our …

We introduce GLM-4-Voice, an intelligent and human-like end-to-end spoken chatbot. It
supports both Chinese and English, engages in real-time voice conversations, and varies …

Challenges in the automated evaluation of Retrieval-Augmented Generation (RAG)
Question-Answering (QA) systems include hallucination problems in domain-specific …

Generative AI applications have played an increasingly significant role in real-time tracking
applications in many domains including, for example, healthcare, consultancy, dialog boxes …

Critique ability, a meta-cognitive capability of humans, presents significant challenges for
LLMs to improve. Recent works primarily rely on supervised fine-tuning (SFT) using critiques …

People have long desired intelligent conversational systems that can provide assistance in
practical scenarios. The latest advancements in large language models (LLMs) are making …