7 papers
SPARE: Single-Pass Annotation with Reference-Guided Evaluation for Automatic Process Supervision and Reward Modelling
Md Imbesat Hassan Rizvi, Xiaodan Zhu, Iryna Gurevych
Process or step-wise supervision has played a crucial role in advancing complex multi-step reasoning capabilities of Large Language Models (LLMs). However, efficient, high-quality…
Preemptive Detection and Correction of Misaligned Actions in LLM Agents
Haishuo Fang, Xiaodan Zhu, Iryna Gurevych
Deploying LLM-based agents in real-life applications often faces a critical challenge: the misalignment between agents' behavior and user intent. Such misalignment may lead agents…
Robust Utility-Preserving Text Anonymization Based on Large Language Models
Tianyu Yang, Xiaodan Zhu, Iryna Gurevych
Anonymizing text that contains sensitive information is crucial for a wide range of applications. Existing techniques face the emerging challenges of the re-identification ability…
Fine-Tuning on Diverse Reasoning Chains Drives Within-Inference CoT Refinement in LLMs
Haritz Puerto, Tilek Chubakov, Xiaodan Zhu +2
Requiring a large language model (LLM) to generate intermediary reasoning steps, known as Chain of Thought (CoT), has been shown to be an effective way of boosting performance. Pre…
DARA: Decomposition-Alignment-Reasoning Autonomous Language Agent for Question Answering over Knowledge Graphs
Haishuo Fang, Xiaodan Zhu, Iryna Gurevych
Answering Questions over Knowledge Graphs (KGQA) is key to well-functioning autonomous language agents in various real-life applications. To improve the neural-symbolic reasoning c…
SpaRC and SpaRP: Spatial Reasoning Characterization and Path Generation for Understanding Spatial Reasoning Capability of Large Language Models
Md Imbesat Hassan Rizvi, Xiaodan Zhu, Iryna Gurevych
Spatial reasoning is a crucial component of both biological and artificial intelligence. In this work, we present a comprehensive study of the capability of current state-of-the-ar…