activity
20242026
most citedEnhancing Table Representations with LLM-powered Synthetic Data Generation

1 citations · 1 across the 8 of their papers we have counts for

collaborators

8 papers

cs.LG2026

QUARTET: Quad-branch cross-Attention and Random-walk Traces for Enhancing Transformers on Relational Graphs

Kyaw Hpone Myint, Nan Jiang, Xiang Li +4

Relational Deep Learning (RDL) models multi-table databases as heterogeneous temporal graphs, and graph transformers currently achieve state-of-the-art performance on benchmarks li…

cs.AI2026

Validity-Aware Jailbreak Evaluation for Large Language Models

Qilong Wu, Sahil Wadhwa, Pranab Mohanty +2

Jailbreak robustness has become central to large language model (LLM) safety evaluation, yet prevailing methodologies rely primarily on refusal behavior, semantic resemblance, and…

cs.IR2026

REPREC: Representation Driven Parameter-Efficient Recommendation System

Harshini Kavuru, Dwipam Katariya, Giri Iyengar +3

Large language models (LLMs) have been applied to sequential recommendation by incorporating collaborative signals through input conditioning or model adaptation. However, existing…

cs.CR2026

Workspace Topology as an Attack Vector in Agentic Coding Assistants

Alexandre G. R. Day, Pradeep Yadlapalli, Sriram Venkatapathy +9

Agentic coding assistants are finding widespread use, not just in new code development but in quickly ingesting and leveraging third-party code. This opens up a risk of malicious c…

cs.IR2026

From Clicks to Intent: Cross-Platform Session Embeddings with LLM-Distilled Taxonomy for Financial Services Recommendations

Dianjing Fan, Yao Li, Kyaw Hpone Myint +4

Sequential user behavior modeling is widely adopted in industrial recommender systems; however, significant gaps remain in financial services, where pre-login web interactions and…

cs.CR2026

CoT-Guard: Small Models for Strong Monitoring

Nirav Diwan, Han Wang, Berkcan Kapusuzoglu +6

Monitoring the chain-of-thought (CoT) of reasoning models is a promising approach for detecting covert misbehavior (i.e., hidden objectives) in code generation tasks. While large m…

cs.LG2025

Towards Scalable Meta-Learning of near-optimal Interpretable Models via Synthetic Model Generations

Kyaw Hpone Myint, Zhe Wu, Alexandre G. R. Day +1

Decision trees are widely used in high-stakes fields like finance and healthcare due to their interpretability. This work introduces an efficient, scalable method for generating sy…

cs.LG2024★ 1 cited

Enhancing Table Representations with LLM-powered Synthetic Data Generation

Dayu Yang, Natawut Monaikul, Amanda Ding +3

In the era of data-driven decision-making, accurate table-level representations and efficient table recommendation systems are becoming increasingly crucial for improving table man…