7 citations · 9 across the 11 of their papers we have counts for
11 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…
Agentic-imodels: Evolving agentic interpretability tools via autoresearch
Chandan Singh, Yan Shuo Tan, Weijia Xu +4
Agentic data science (ADS) systems are rapidly improving their capability to autonomously analyze, fit, and interpret data, potentially moving towards a future where agents conduct…
Test-Time Learning with an Evolving Library
Weijia Xu, Alessandro Sordoni, Chandan Singh +4
We introduce EvoLib, a test-time learning framework that enables large language models to accumulate, reuse, and evolve knowledge across problem instances without parameter updates…
Echoes in AI: Quantifying lack of plot diversity in LLM outputs
Weijia Xu, Nebojsa Jojic, Sudha Rao +2
With rapid advances in large language models (LLMs), there has been an increasing application of LLMs in creative content ideation and generation. A critical question emerges: can…
Game Plot Design with an LLM-powered Assistant: An Empirical Study with Game Designers
Seyed Hossein Alavi, Weijia Xu, Nebojsa Jojic +6
We introduce GamePlot, an LLM-powered assistant that supports game designers in crafting immersive narratives for turn-based games, and allows them to test these games through a co…
fLSA: Learning Semantic Structures in Document Collections Using Foundation Models
Weijia Xu, Nebojsa Jojic, Nicolas Le Roux
Humans can learn to solve new tasks by inducing high-level strategies from example solutions to similar problems and then adapting these strategies to solve unseen problems. Can we…
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…