3 citations · 3 across the 7 of their papers we have counts for
9 papers
Planning Commitment of LLM under Partial Observability
Cassie Huang, Zhanwei Cao, Yeawon Lee +7
LLM-based planning agents commit to plans of different lengths before interacting with a partially observable environment. Some aggressively commit to a long plan based on assumpti…
SafeDepth: Safety-Aware Token-Level Adaptive Computation
Nizhang Li, Ian G. Harris
Recent studies suggest that not every token needs to pass through all Transformer layers, motivating token-level adaptive models that selectively skip layers to reduce computation.…
Asymmetric Capacity Allocation in Self-Refinement Pipelines
Zhuoyi Yang, Ian G. Harris, Salar Hashemitaheri +7
Self-refinement, typically structured as generation, critique, and revision, is a widely adopted paradigm for improving LLM generation and serves as a core mechanism in many LLM ag…
Compress to Focus: Efficient Coordinate Compression for Policy Optimization in Multi-Turn GUI Agents
Yurun Song, Jiong Yin, Rongjunchen Zhang +1
Multi-turn GUI agents enable complex task completion through sequential decision-making, but suffer from severe context inflation as interaction history accumulates. Existing strat…
Fine-Tuning vs. RAG for Multi-Hop Question Answering with Novel Knowledge
Zhuoyi Yang, Yurun Song, Iftekhar Ahmed +1
Multi-hop question answering is widely used to evaluate the reasoning capabilities of large language models (LLMs), as it requires integrating multiple pieces of supporting knowled…
AMAQ: Adaptive Mixed-bit Activation Quantization for Collaborative Parameter Efficient Fine-tuning
Yurun Song, Zhuoyi Yang, Ian G. Harris +1
Large Language Models (LLMs) are scaling rapidly, creating significant challenges for collaborative server client distributed training, particularly in terms of communication effic…
CoopQ: Cooperative Game Inspired Layerwise Mixed Precision Quantization for LLMs
Junchen Zhao, Ali Derakhshan, Jayden Kana Hyman +3
Large Language Models (LLMs) promise impressive capabilities, yet their multi-billion-parameter scale makes on-device or low-resource deployment prohibitive. Mixed-precision quanti…
ShareLoRA: Parameter Efficient and Robust Large Language Model Fine-tuning via Shared Low-Rank Adaptation
Yurun Song, Junchen Zhao, Ian G. Harris +1
In this paper, we introduce \textbf{Share}d \textbf{Lo}w \textbf{R}ank \textbf{A}daptation (ShareLoRA), a Large Language Model (LLM) fine-tuning technique that balances parameter e…
LinguaLinked: A Distributed Large Language Model Inference System for Mobile Devices
Junchen Zhao, Yurun Song, Simeng Liu +2
Deploying Large Language Models (LLMs) locally on mobile devices presents a significant challenge due to their extensive memory requirements. In this paper, we introduce LinguaLink…