Accounting for Variations in Speech Emotion Recognition with Nonparametric Hierarchical Neural Network. - Lance Ying; Amrit Romana; Emily Mower Provost (CoRR, 2021)

A Bayesian Drift-Diffusion Model of Schachter-Singer's Two-Factor Theory of Emotion. - Lance Ying; Audrey Michal; Jun Zhang (CogSci, 2022)

The Neuro-Symbolic Inverse Planning Engine (NIPE): Modeling Probabilistic Social Inferences from Linguistic Inputs. - Lance Ying; Katherine M. Collins; Megan Wei; Cedegao E. Zhang; Tan Zhi-Xuan; Adrian Weller; Joshua B. Tenenbaum; Lionel Wong (CoRR, 2023)

Inferring the Goals of Communicating Agents from Actions and Instructions. - Lance Ying; Tan Zhi-Xuan; Vikash Mansinghka 001; Joshua B. Tenenbaum (CoRR, 2023)

Pragmatic Instruction Following and Goal Assistance via Cooperative Language-Guided Inverse Planning. - Tan Zhi-Xuan; Lance Ying; Vikash Mansinghka 001; Joshua B. Tenenbaum (AAMAS, 2024)

GOMA: Proactive Embodied Cooperative Communication via Goal-Oriented Mental Alignment. - Lance Ying; Kunal Jha; Shivam Aarya; Joshua B. Tenenbaum; Antonio Torralba 001; Tianmin Shu (IROS, 2024)

Grounding Language about Belief in a Bayesian Theory-of-Mind. - Lance Ying; Tan Zhi-Xuan; Lionel Wong; Vikash Mansinghka 001; Joshua B. Tenenbaum (CoRR, 2024)

Understanding Epistemic Language with a Bayesian Theory of Mind. - Lance Ying; Tan Zhi-Xuan; Lionel Wong; Vikash Mansinghka 001; Joshua B. Tenenbaum (CoRR, 2024)

SIFToM: Robust Spoken Instruction Following through Theory of Mind. - Lance Ying; Jason Xinyu Liu; Shivam Aarya; Yizirui Fang; Stefanie Tellex; Joshua B. Tenenbaum; Tianmin Shu (CoRR, 2024)

Understanding Epistemic Language with a Language-augmented Bayesian Theory of Mind. - Lance Ying; Tan Zhi-Xuan; Lionel Wong; Vikash Mansinghka 001; Joshua B. Tenenbaum (Trans. Assoc. Comput. Linguistics, 2025)

Hypothesis-Driven Theory-of-Mind Reasoning for Large Language Models. - Hyunwoo Kim 002; Melanie Sclar; Tan Zhi-Xuan; Lance Ying; Sydney Levine; Yang Liu; Joshua B. Tenenbaum; Yejin Choi 001 (CoRR, 2025)

On Benchmarking Human-Like Intelligence in Machines. - Lance Ying; Katherine M. Collins; Lionel Wong; Ilia Sucholutsky; Ryan Liu 001; Adrian Weller; Tianmin Shu; Thomas L. Griffiths 001; Joshua B. Tenenbaum (CoRR, 2025)

Belief Attribution as Mental Explanation: The Role of Accuracy, Informativity, and Causality. - Lance Ying; Almog Hillel; Ryan Truong; Vikash K. Mansinghka; Joshua B. Tenenbaum; Tan Zhi-Xuan (CoRR, 2025)

What's in the Box? Reasoning about Unseen Objects from Multimodal Cues. - Lance Ying; Daniel Xu; Alicia Zhang; Katherine M. Collins; Max H. Siegel; Joshua B. Tenenbaum (CoRR, 2025)

Language-Informed Synthesis of Rational Agent Models for Grounded Theory-of-Mind Reasoning On-The-Fly. - Lance Ying; Ryan Truong; Katherine M. Collins; Cedegao E. Zhang; Megan Wei; Tyler Brooke-Wilson; Tan Zhi-Xuan; Lionel Wong; Joshua B. Tenenbaum (CoRR, 2025)

Adaptive Social Learning using Theory of Mind. - Lance Ying; Ryan Truong; Joshua B. Tenenbaum; Samuel J. Gershman (CoRR, 2025)

Modeling Open-World Cognition as On-Demand Synthesis of Probabilistic Models. - Lionel Wong; Katherine M. Collins; Lance Ying; Cedegao E. Zhang; Adrian Weller; Tobias Gerstenberg; Timothy O'Donnell; Alexander K. Lew; Jacob Andreas; Joshua B. Tenenbaum; Tyler Brooke-Wilson (CoRR, 2025)

Assessing Adaptive World Models in Machines with Novel Games. - Lance Ying; Katherine M. Collins; Prafull Sharma; Cedric Colas; Kaiya Ivy Zhao; Adrian Weller; Zenna Tavares; Phillip Isola; Samuel J. Gershman; Jacob Andreas; Thomas L. Griffiths 001; François Chollet; et al. (CoRR, 2025)