As Large Language Models (LLMs) continue to advance in natural language processing
(NLP), their ability to stably follow instructions in long-context inputs has become crucial for …

Despite the recent advancement of Large Langauge Models (LLMs), they struggle with
complex queries often involving multiple conditions, common in real-world scenarios. We …

It is crucial for large language models (LLMs) to follow instructions that involve multiple
constraints. However, soft constraints are semantically related and difficult to verify through …

Evaluating the creativity of large language models (LLMs) in story writing is difficult because
LLM-generated stories could seemingly look creative but be very similar to some existing …

We introduce Baichuan Alignment, a detailed analysis of the alignment techniques
employed in the Baichuan series of models. This represents the industry's first …

In the realm of large language models (LLMs), the ability of models to accurately follow
instructions is paramount as more agents and applications leverage LLMs for construction …

Fine granularity is an essential requirement for controllable text generation, which has seen
rapid growth with the ability of LLMs. However, existing methods focus mainly on a small set …

In this study, we propose a hierarchical task learning framework based on Large Language
Models (LLMs) to improve the performance in spoken language understanding (SLU). Our …

Instruction following is a key capability for LLMs. However, recent studies have shown that
LLMs often struggle with instructions containing multiple constraints (eg a request to create a …