activity
20242026
most citedSLOT: Structuring the Output of Large Language Models

2 citations · 4 across the 5 of their papers we have counts for

collaborators

12 papers

cs.CL2026

Defragmenting Language Models: An Interpretability-based Approach for Vocabulary Expansion

Maitrey Mehta, Nishant Subramani, Zhichao Xu +2

All languages are equal; when it comes to tokenization, some are more equal than others. Tokens are the hidden currency that dictate the cost and latency of access to contemporary…

cs.LG2025

TransactionGPT

Yingtong Dou, Zhimeng Jiang, Tianyi Zhang +26

We present TransactionGPT (TGPT), a foundation model for consumer transaction data within one of the world's largest payment networks. TGPT is designed to understand and generate t…

cs.CL2025

Reinforcement Mid-Training

Yijun Tian, Shaoyu Chen, Zhichao Xu +4

The development of state-of-the-art large language models is commonly understood as a two-stage process involving pre-training and post-training. We point out the need for an addit…

cs.IR2025

ConvMix: A Mixed-Criteria Data Augmentation Framework for Conversational Dense Retrieval

Fengran Mo, Jinghan Zhang, Yuchen Hui +4

Conversational search aims to satisfy users' complex information needs via multiple-turn interactions. The key challenge lies in revealing real users' search intent from the contex…

cs.CL2025

Distillation versus Contrastive Learning: How to Train Your Rerankers

Zhichao Xu, Zhiqi Huang, Shengyao Zhuang +1

Training effective text rerankers is crucial for information retrieval. Two strategies are widely used: contrastive learning (optimizing directly on ground-truth labels) and knowle…

cs.CL20251 cited

Found in Translation: Measuring Multilingual LLM Consistency as Simple as Translate then Evaluate

Ashim Gupta, Maitrey Mehta, Zhichao Xu +1

Large language models (LLMs) provide detailed and impressive responses to queries in English. However, are they really consistent at responding to the same query in other languages…