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cs.CL2026
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…
cs.CL2026
References Improve LLM Alignment in Non-Verifiable Domains
Kejian Shi, Yixin Liu, Peifeng Wang +3
While Reinforcement Learning with Verifiable Rewards (RLVR) has shown strong effectiveness in reasoning tasks, it cannot be directly applied to non-verifiable domains lacking groun…
cs.CL2024
ReIFE: Re-evaluating Instruction-Following Evaluation
Yixin Liu, Kejian Shi, Alexander R. Fabbri +5
The automatic evaluation of instruction following typically involves using large language models (LLMs) to assess response quality. However, there is a lack of comprehensive evalua…