1 citations · 2 across the 15 of their papers we have counts for
16 papers
Reading Right, Acting Wrong: Diagnosing Decision Failures of System One Models in Agent Loops
Yubo Li, Ramayya Krishnan, Rema Padman
System One models choose an agent's next action by scoring a supplied set of options in a single pass. This makes them fast and cheap, but when they choose wrongly there is nothing…
Latent Commonality Expectation-Maximisation for Box-supervised Tree Crown Instance Segmentation
Thomas Pitts, Kunqi Li, Bin Liang
Individual tree crown segmentation from aerial imagery underpins tree-level carbon accounting, biodiversity, and restoration monitoring at landscape scale. However, existing models…
LLMs Know the Constraint But Do Not Use It: Activation Bottlenecks in Pragmatic Constraint Reasoning
Yubo Li, Ramayya Krishnan, Rema Padman
When a salient surface cue competes with an implicit feasibility constraint, LLMs often fail -- but aggregate accuracy conflates genuine constraint inference with conservative defa…
Auditing Institutional Heterogeneity for Generative AI in Patient Education: A Large-Scale Study of 102 US Transplant Handbooks
Yubo Li, Rema Padman, Ramayya Krishnan
Health systems are rapidly deploying generative-AI assistants that answer patient questions from institution-authored education materials, on the premise that grounding in local co…
The Chain Holds, the Answer Folds: Trace-Answer Dissociation in Reasoning Models Under Adversarial Pressure
Yubo Li, Ramayya Krishnan, Rema Padman
Reasoning models are evaluated on single-turn benchmarks but deployed in multi-turn dialogue, where users push back on correct answers. Under sustained adversarial pressure we find…
Same Question, Different Source, Different Answer: Auditing Source-Dependence in Medical Multi-Source RAG
Yubo Li, Rema Padman, Ramayya Krishnan
A retrieval-augmented generation (RAG) system deployed over a multi-author institutional corpus can give a different answer to the same question depending on which source it retrie…
When Documents Disagree: Measuring Institutional Variation in Transplant Guidance with Retrieval-Augmented Language Models
Yubo Li, Ramayya Krishnan, Rema Padman
Patient education materials for solid-organ transplantation vary substantially across U.S. centers, yet no systematic method exists to quantify this heterogeneity at scale. We intr…
Consistency of Large Reasoning Models Under Multi-Turn Attacks
Yubo Li, Ramayya Krishnan, Rema Padman
Large reasoning models with reasoning capabilities achieve state-of-the-art performance on complex tasks, but their robustness under multi-turn adversarial pressure remains underex…
The Model Says Walk: Measuring whether LLMs Condition on Hidden Constraints
Yubo Li, Lu Zhang, Tianchong Jiang +2
Asked whether to walk or drive to a car wash 50 m away, most language models say walk, forgetting that the car has to be there. Such failures are usually measured by accuracy on qu…
Closing Reasoning Gaps in Clinical Agents with Differential Reasoning Learning
Jinsong Liu, Yuhang Jiang, Ramayya Krishnan +3
Clinical decision support requires not only correct answers but also clinically valid reasoning. We propose Differential Reasoning Learning (DRL), a framework that improves clinica…
Chain-of-Influence: Tracing Interdependencies Across Time and Features in Clinical Predictive Modelings
Yubo Li, Rema Padman
Modeling clinical time-series data is hampered by the challenge of capturing latent, time-varying dependencies among features. State-of-the-art approaches often rely on black-box m…
Time-To-Inconsistency: A Survival Analysis of Large Language Model Robustness to Adversarial Attacks
Yubo Li, Ramayya Krishnan, Rema Padman
Large Language Models (LLMs) have revolutionized conversational AI, yet their robustness in extended multi-turn dialogues remains poorly understood. Existing evaluation frameworks…
Beyond Single-Turn: A Survey on Multi-Turn Interactions with Large Language Models
Yubo Li, Xiaobin Shen, Yidi Miao +4
Recent advances in large language models (LLMs) have substantially improved single-turn task performance, yet real-world applications increasingly demand sophisticated multi-turn i…
Can LLMs Support Medical Knowledge Imputation? An Evaluation-Based Perspective
Xinyu Yao, Aditya Sannabhadti, Holly Wiberg +2
Medical knowledge graphs (KGs) are essential for clinical decision support and biomedical research, yet they often exhibit incompleteness due to knowledge gaps and structural limit…
Firm or Fickle? Evaluating Large Language Models Consistency in Sequential Interactions
Yubo Li, Yidi Miao, Xueying Ding +2
Large Language Models (LLMs) have shown remarkable capabilities across various tasks, but their deployment in high-stake domains requires consistent and coherent behavior across mu…
No Black Box Anymore: Demystifying Clinical Predictive Modeling with Temporal-Feature Cross Attention Mechanism
Yubo Li, Xinyu Yao, Rema Padman
Despite the outstanding performance of deep learning models in clinical prediction tasks, explainability remains a significant challenge. Inspired by transformer architectures, we…