From the 1 of 8 linked papers with an AI index.
8 papers
Track, Rank, Crack: Epistemic Working Memory Scales Multi-Hop Reasoning in Language Agents
Ning Liu
The paper introduces SLEUTH, a system that gives language agents an explicit epistemic working memory to track confirmed facts, rank hypotheses, and manage open questions, improvin…
LLMs as a Jury: Cross-Model Consensus Can Outperform Process Reward Models for LLM Reasoning
Ning Liu
Selecting the correct answer from a pool of candidate reasoning chains is the engine of test-time scaling, yet the standard selectors each carry a cost: self-consistency inherits t…
Eluna: An Agentic LLM System for Automating Warehouse Operations with Reasoning and Task Execution
Ning Liu, Kalle Kujanpää, Zhaoxuan Zhu +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…
Rethinking Flexible Graph Similarity Computation: One-step Alignment with Global Guidance
Zhouyang Liu, Ning Liu, Yixin Chen +3
Graph Edit Distance (GED) is a widely used measure of graph similarity, valued for its flexibility in encoding domain knowledge through operation costs. However, existing learning-…