100 citations · 169 across the 7 of their papers we have counts for
5 papers · 1 filter
SynAct: Synergistic Active Feedback Learning for LLM Agents
Ning Liu, Ian Li, Kristina Klinkner
LLM agents executing multi-step workflows fail in two fundamentally different ways: recoverable slips, which further attempts can repair, and knowledge gaps, which retrying cannot…
Eluna: An Agentic LLM System for Automating Warehouse Operations with Reasoning and Task Execution
Ning Liu, P Aditya Sreekar, Kalle Kujanpää +11
Warehouse operations are governed by Standard Operating Procedures (SOPs) that encode complex, multi-system decision logic, which must be executed reliably under strict time constr…
Tool-Making and Self-Evolving LLM Agents in Low-Latency Systems
Kalle Kujanpää, Ning Liu, Shahnawaz Alam +4
Production LLM agents often waste latency and reliability by regenerating code for the same procedural steps on every request. We replace this inference-time coding loop with an ag…
Beyond Pairs: Your Language Model is Secretly Optimizing a Preference Graph
Ning Liu, Chuanneng Sun, Kristina Klinkner +1
Direct Preference Optimization (DPO) aligns language models using pairwise preference comparisons, offering a simple and effective alternative to Reinforcement Learning (RL) from h…
Learning to Staff: Offline Reinforcement Learning and Fine-Tuned LLMs for Warehouse Staffing Optimization
Kalle Kujanpää, Yuying Zhu, Kristina Klinkner +1
We investigate machine learning approaches for optimizing real-time staffing decisions in semi-automated warehouse sortation systems. Operational decision-making can be supported a…