2 citations · 2 across the 9 of their papers we have counts for
9 papers
Reinforcement Learning with Evolving Rubrics as Rewards for Audio Reasoning
Fangxu Yu, Tao Feng, Dehai Min +6
Audio reasoning is essential for machine understanding of the acoustic world. Reinforcement learning with verifiable rewards can elicit such reasoning, yet existing reward designs…
Weak-to-Strong On-Policy Distillation
Fangxu Yu, Weijia Xu, Michael Xu +2
On-policy distillation (OPD), which aligns a student with the teacher's token-level distribution on the student's own rollouts, is an effective paradigm for transferring capabiliti…
Rushes: A Human Preference Dataset for Pluralistic Alignment
Michael Xu, Jorge Leandro, Sudha Rao +5
We introduce Rushes, a dataset and benchmark for studying revealed human engagement preferences in interactive narrative environments. Rushes is collected through a game interface…
GFlowRL: Scaling Distribution-Matching RL to Large Language Models
Xiaodong Liu, Michael Xu, Jack W. Stokes +3
Generative Flow Networks (GFlowNets) offer a promising alternative to reward-maximizing reinforcement learning (RL) for large reasoning models, encouraging diverse reasoning paths…
MineNPC-Task: Task Suite for Memory-Aware Minecraft Agents
Tamil Sudaravan Mohan Doss, Michael Xu, Sudha Rao +2
We present MineNPC-Task, a user-authored benchmark and evaluation harness for testing memory-aware, mixed-initiative LLM agents in open-world Minecraft. Rather than relying on synt…
Adversarial Distilled Retrieval-Augmented Guarding Model for Online Malicious Intent Detection
Yihao Guo, Haocheng Bian, Liutong Zhou +16
With the deployment of Large Language Models (LLMs) in interactive applications, online malicious intent detection has become increasingly critical. However, existing approaches fa…
Collaborative Quest Completion with LLM-driven Non-Player Characters in Minecraft
Sudha Rao, Weijia Xu, Michael Xu +5
The use of generative AI in video game development is on the rise, and as the conversational and other capabilities of large language models continue to improve, we expect LLM-driv…
Player-Driven Emergence in LLM-Driven Game Narrative
Xiangyu Peng, Jessica Quaye, Sudha Rao +10
We explore how interaction with large language models (LLMs) can give rise to emergent behaviors, empowering players to participate in the evolution of game narratives. Our testbed…
GENEVA: GENErating and Visualizing branching narratives using LLMs
Jorge Leandro, Sudha Rao, Michael Xu +4
Dialogue-based Role Playing Games (RPGs) require powerful storytelling. The narratives of these may take years to write and typically involve a large creative team. In this work, w…