Papers by Sirui Zou
PersonaForge: Psychology-Grounded Dual-Process Architecture for Personality-Consistent Role-Playing Agents (2026.findings-acl)
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| Challenge: | Existing approaches to role-playing with Large Language Models lack consistency across long conversations. |
| Approach: | They propose a three-layer personality architecture grounded in psychological theory and a dual-process generation mechanism inspired by cognitive science to solve this problem. |
| Outcome: | The proposed framework reduces drift over 50-turn conversations by reducing personality consistency . human evaluation confirms more authentic and psychologically coherent character behaviors. |
Capturing Nuanced Preferences: Preference-Aligned Distillation for Small Language Models (2025.findings-acl)
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| Challenge: | Existing methods for aligning small language models with human values model preference knowledge from large language models (LLMs) however, this limitation hinders student SLMs from capturing nuanced preferences for multiple responses. |
| Approach: | They propose a framework which models teacher's preference knowledge as a probability distribution over all potential preferences, thereby providing more nuanced supervisory signals. |
| Outcome: | The proposed framework outperforms existing methods on four benchmark tasks and achieves 20% improvement on AlpacaEval 2 and Arena-Hard. |
RAG over Tables: Hierarchical Memory Index, Multi-Stage Retrieval, and Benchmarking (2026.findings-acl)
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| Challenge: | Retrieval-Augmented Generation (RAG) integrates knowledge from tables with an external knowledge base to improve the answer relevance and accuracy. |
| Approach: | They propose a table-corpora-aware RAG framework called T-RAG to integrate external knowledge into Large Language Models (LLMs) they then develop a multi-table question answering benchmark called MultiTableQA which spans 3 different task types, 57,193 tables, and 23,758 questions in total. |
| Outcome: | The proposed framework achieves state-of-the-art accuracy, recall, and runtime performance, with improvements of up to 9.4%. |