203 citations · 224 across the 17 of their papers we have counts for
18 papers
Splicing Hints into Reasoning Traces: Learning from Demonstrator Failures
Hamed Mahdavi, Pouria Mahdavinia, Majid Farhadi +1
Reinforcement learning with verifiable rewards improves mathematical reasoning when a final answer can be checked, but a correct answer does not certify the derivation behind it, a…
PAC-Bayes Beyond Parameter Space: Behavioral Equivalence, Z-Information, and Exact Complexity Decomposition
Vasant G. Honavar, Satish Kumar Keshri, Neil Ashtekar +1
PAC-Bayes theory provides generalization guarantees by controlling the Kullback--Leibler (KL) divergence between posterior and prior distributions over a chosen hypothesis represen…
Skin-R1: Clinical Knowledge-Guided Dermatological Diagnosis Using Vision-Language Models
Zehao Liu, Weijieying Ren, Jipeng Zhang +4
Vision--language models (VLMs) have recently shown promise for assisting clinical reasoning in dermatological diagnosis. However, their trustworthiness and clinical utility remain…
CombiGraph-Vis: A Curated Multimodal Olympiad Benchmark for Discrete Mathematical Reasoning
Hamed Mahdavi, Pouria Mahdavinia, Alireza Farhadi +7
State-of-the-art (SOTA) LLMs have progressed from struggling on proof-based Olympiad problems to solving most of the IMO 2025 problems, with leading systems reportedly handling 5 o…
RefGrader: Automated Grading of Mathematical Competition Proofs using Agentic Workflows
Hamed Mahdavi, Pouria Mahdavinia, Samira Malek +7
State-of-the-art (SOTA) LLMs have progressed from struggling on proof-based Olympiad problems to solving most of the IMO 2025 problems, with leading systems reportedly handling 5 o…
A Comprehensive Survey of Electronic Health Record Modeling: From Deep Learning Approaches to Large Language Models
Weijieying Ren, Jingxi Zhu, Zehao Liu +2
Artificial intelligence (AI) has demonstrated significant potential in transforming healthcare through the analysis and modeling of electronic health records (EHRs). However, the i…
DiaLLMs: EHR Enhanced Clinical Conversational System for Clinical Test Recommendation and Diagnosis Prediction
Weijieying Ren, Tianxiang Zhao, Lei Wang +2
Recent advances in Large Language Models (LLMs) have led to remarkable progresses in medical consultation. However, existing medical LLMs overlook the essential role of Electronic…
Brains vs. Bytes: Evaluating LLM Proficiency in Olympiad Mathematics
Hamed Mahdavi, Alireza Hashemi, Majid Daliri +6
Recent advances in large language models (LLMs) have shown impressive progress in mathematical reasoning tasks. However, current evaluation benchmarks predominantly focus on the ac…
A practical guide to machine learning interatomic potentials -- Status and future
Ryan Jacobs, Dane Morgan, Siamak Attarian +27
The rapid development and large body of literature on machine learning interatomic potentials (MLIPs) can make it difficult to know how to proceed for researchers who are not exper…
Deep Learning within Tabular Data: Foundations, Challenges, Advances and Future Directions
Weijieying Ren, Tianxiang Zhao, Yuqing Huang +1
Tabular data remains one of the most prevalent data types across a wide range of real-world applications, yet effective representation learning for this domain poses unique challen…
C-HDNet: Hyperdimensional Computing for Causal Effect Estimation from Observational Data Under Network Interference
Abhishek Dalvi, Neil Ashtekar, Vasant Honavar
We address the problem of estimating causal effects from observational data in the presence of network confounding, a setting where both treatment assignment and observed outcomes…
Regression with Large Language Models for Materials and Molecular Property Prediction
Ryan Jacobs, Maciej P. Polak, Lane E. Schultz +3
We demonstrate the ability of large language models (LLMs) to perform material and molecular property regression tasks, a significant deviation from the conventional LLM use case.…
MolBind: Multimodal Alignment of Language, Molecules, and Proteins
Teng Xiao, Chao Cui, Huaisheng Zhu +1
Recent advancements in biology and chemistry have leveraged multi-modal learning, integrating molecules and their natural language descriptions to enhance drug discovery. However,…
Causal Effect Estimation Using Random Hyperplane Tessellations
Abhishek Dalvi, Neil Ashtekar, Vasant Honavar
Matching is one of the simplest approaches for estimating causal effects from observational data. Matching techniques compare the observed outcomes across pairs of individuals with…
3M-Diffusion: Latent Multi-Modal Diffusion for Language-Guided Molecular Structure Generation
Huaisheng Zhu, Teng Xiao, Vasant G Honavar
Generating molecular structures with desired properties is a critical task with broad applications in drug discovery and materials design. We propose 3M-Diffusion, a novel multi-mo…
Hyperdimensional Representation Learning for Node Classification and Link Prediction
Abhishek Dalvi, Vasant Honavar
We introduce Hyperdimensional Graph Learner (HDGL), a novel method for node classification and link prediction in graphs. HDGL maps node features into a very high-dimensional space…
EsaCL: Efficient Continual Learning of Sparse Models
Weijieying Ren, Vasant G Honavar
A key challenge in the continual learning setting is to efficiently learn a sequence of tasks without forgetting how to perform previously learned tasks. Many existing approaches t…
The Dynamical Gaussian Process Latent Variable Model in the Longitudinal Scenario
Thanh Le, Vasant Honavar
The Dynamical Gaussian Process Latent Variable Models provide an elegant non-parametric framework for learning the low dimensional representations of the high-dimensional time-seri…