1 citations · 2 across the 3 of their papers we have counts for
4 papers
Muse Glimmer 30B: An On-Device Agentic Model
Arash Ebrahim Abtahizadeh, Muna Aghamelu, Adil Ahmed +327
We introduce Muse Glimmer, an open-source 30B parameter causal language model with perception encoder, purpose-built for autonomous agentic tasks on consumer hardware. Muse Glimmer…
SCALAR: Learning and Composing Skills through LLM Guided Symbolic Planning and Deep RL Grounding
Renos Zabounidis, Yue Wu, Simon Stepputtis +4
LM-based agents excel when given high-level action APIs but struggle to ground language into low-level control. Prior work has LLMs generate skills or reward functions for RL, but…
AgentKit: Structured LLM Reasoning with Dynamic Graphs
Yue Wu, Yewen Fan, So Yeon Min +6
We propose an intuitive LLM prompting framework (AgentKit) for multifunctional agents. AgentKit offers a unified framework for explicitly constructing a complex "thought process" f…
SmartPlay: A Benchmark for LLMs as Intelligent Agents
Yue Wu, Xuan Tang, Tom M. Mitchell +1
Recent large language models (LLMs) have demonstrated great potential toward intelligent agents and next-gen automation, but there currently lacks a systematic benchmark for evalua…