activity
20242026
collaborators

7 papers

cs.NE2026

Analysis of Memory-Runtime Trade-offs in Caching Strategies for Genetic Programming Symbolic Regression

Jiaming Shi, Kei Sen Fong, Mehul Motani

Genetic Programming Symbolic Regression (GPSR) generates mathematical expressions to model input-output relationships using an evolutionary process. A significant challenge in GPSR…

cs.LG2026

On the effectiveness of reward functions in reinforcement learning for confidence calibration of large language models

Chee Heng Tan, Zhuoyi Lin, Mehul Motani +1

In this paper, we consider the setting where large language models (LLMs) are trained using reinforcement learning (RL) to simultaneously improve reasoning accuracy and verbalize i…

cs.IT2026

Age of Information under Source-Aware Truncated ARQ in Multi-Source Wireless Status Updating

Tianci Zhang, Aobo Liu, Zhengchuan Chen +4

This paper studies information timeliness in multi-source wireless Internet of Things (IoT) status updating systems under a truncated Automatic Repeat reQuest (ARQ) protocol. We pr…

cs.LG2026

Teaching the Teacher: The Role of Teacher-Student Smoothness Alignment in Genetic Programming-based Symbolic Distillation

Soumyadeep Dhar, Kei Sen Fong, Mehul Motani

Obtaining human-readable symbolic formulas via genetic programming-based symbolic distillation of a deep neural network trained on the target dataset presents a promising yet under…

cs.LG2025

Tab-PET: Graph-Based Positional Encodings for Tabular Transformers

Yunze Leng, Rohan Ghosh, Mehul Motani

Supervised learning with tabular data presents unique challenges, including low data sizes, the absence of structural cues, and heterogeneous features spanning both categorical and…

cs.IT2025

Absorbing Markov Chain-Based Analysis of Age of Information in Discrete-Time Dual-Queue Systems

Yifan Feng, Nail Akar, Zhengchuan Chen +1

Status update systems require the timely collection of sensing information for which deploying multiple sensors/servers to obtain diversity gains is considered as a promising solut…