55 citations · 90 across the 8 of their papers we have counts for
8 papers
ConvApparel: A Benchmark Dataset and Validation Framework for User Simulators in Conversational Recommenders
Ofer Meshi, Krisztian Balog, Sally Goldman +5
The promise of LLM-based user simulators to improve conversational AI is hindered by a critical "realism gap," leading to systems that are optimized for simulated interactions, but…
MiniScope: Authorizing Agents with Least-Privilege Permissions
Jinhao Zhu, Kevin Tseng, Gil Vernik +4
AI agents are increasingly granted autonomous access to sensitive user data and third-party services, making effective permission management a critical security challenge. Existing…
LLMs Can Easily Learn to Reason from Demonstrations Structure, not content, is what matters!
Dacheng Li, Shiyi Cao, Tyler Griggs +9
Large reasoning models (LRMs) tackle complex reasoning problems by following long chain-of-thoughts (Long CoT) that incorporate reflection, backtracking, and self-validation. Howev…
Specifications: The missing link to making the development of LLM systems an engineering discipline
Ion Stoica, Matei Zaharia, Joseph Gonzalez +8
Despite the significant strides made by generative AI in just a few short years, its future progress is constrained by the challenge of building modular and robust systems. This ca…
GoEX: Perspectives and Designs Towards a Runtime for Autonomous LLM Applications
Shishir G. Patil, Tianjun Zhang, Vivian Fang +7
Large Language Models (LLMs) are evolving beyond their classical role of providing information within dialogue systems to actively engaging with tools and performing actions on rea…
LLoCO: Learning Long Contexts Offline
Sijun Tan, Xiuyu Li, Shishir Patil +5
Processing long contexts remains a challenge for large language models (LLMs) due to the quadratic computational and memory overhead of the self-attention mechanism and the substan…
RAFT: Adapting Language Model to Domain Specific RAG
Tianjun Zhang, Shishir G. Patil, Naman Jain +4
Pretraining Large Language Models (LLMs) on large corpora of textual data is now a standard paradigm. When using these LLMs for many downstream applications, it is common to additi…
MemGPT: Towards LLMs as Operating Systems
Charles Packer, Sarah Wooders, Kevin Lin +4
Large language models (LLMs) have revolutionized AI, but are constrained by limited context windows, hindering their utility in tasks like extended conversations and document analy…