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What are the essential factors in crafting effective long context multi-hop instruction datasets? insights and best practices
Recent advancements in large language models (LLMs) with extended context windows
have significantly improved tasks such as information extraction, question answering, and …
have significantly improved tasks such as information extraction, question answering, and …
Large Model Agents: State-of-the-Art, Cooperation Paradigms, Security and Privacy, and Future Trends
Large Model (LM) agents, powered by large foundation models such as GPT-4 and DALL-E
2, represent a significant step towards achieving Artificial General Intelligence (AGI). LM …
2, represent a significant step towards achieving Artificial General Intelligence (AGI). LM …
Text2World: Benchmarking Large Language Models for Symbolic World Model Generation
Recently, there has been growing interest in leveraging large language models (LLMs) to
generate symbolic world models from textual descriptions. Although LLMs have been …
generate symbolic world models from textual descriptions. Although LLMs have been …
A Cognitive Writing Perspective for Constrained Long-Form Text Generation
Like humans, Large Language Models (LLMs) struggle to generate high-quality long-form
text that adheres to strict requirements in a single pass. This challenge is unsurprising, as …
text that adheres to strict requirements in a single pass. This challenge is unsurprising, as …
On the Structural Memory of LLM Agents
Memory plays a pivotal role in enabling large language model~(LLM)-based agents to
engage in complex and long-term interactions, such as question answering (QA) and …
engage in complex and long-term interactions, such as question answering (QA) and …
" Ghost of the past": identifying and resolving privacy leakage from LLM's memory through proactive user interaction
Memories, encompassing past inputs in context window and retrieval-augmented
generation (RAG), frequently surface during human-LLM interactions, yet users are often …
generation (RAG), frequently surface during human-LLM interactions, yet users are often …