Search Results for author:
Found 7 papers, 6 papers with code
KnowAgent: Knowledge-Augmented Planning for LLM-Based Agents
Large Language Models (LLMs) have demonstrated great potential in complex reasoning tasks, yet they fall short when tackling more sophisticated challenges, especially when interacting with environments through generating executable actions.
EasyInstruct: An Easy-to-use Instruction Processing Framework for Large Language Models
In recent years, instruction tuning has gained increasing attention and emerged as a crucial technique to enhance the capabilities of Large Language Models (LLMs).
OceanGPT: A Large Language Model for Ocean Science Tasks
Ocean science, which delves into the oceans that are reservoirs of life and biodiversity, is of great significance given that oceans cover over 70% of our planet's surface.
Layout and Task Aware Instruction Prompt for Zero-shot Document Image Question Answering
Instead, in this paper, we find that instruction-tuning language models like Claude and ChatGPT can understand layout by spaces and line breaks.
Ranked #8 on
Visual Question Answering (VQA)
on DocVQA test
LLMs for Knowledge Graph Construction and Reasoning: Recent Capabilities and Future Opportunities
We engage in experiments across eight diverse datasets, focusing on four representative tasks encompassing entity and relation extraction, event extraction, link prediction, and question-answering, thereby thoroughly exploring LLMs' performance in the domain of construction and inference.
A Concept Knowledge Graph for User Next Intent Prediction at Alipay
This paper illustrates the technologies of user next intent prediction with a concept knowledge graph.
Reasoning with Language Model Prompting: A Survey
Reasoning, as an essential ability for complex problem-solving, can provide back-end support for various real-world applications, such as medical diagnosis, negotiation, etc.
