1 citations · 2 across the 10 of their papers we have counts for
13 papers
Differential Privacy Protected Preference Alignment on Survey Derived Data
Xiuyuan Qi, Yi Wang, Wenjie Wang
Preference alignment enables language models to better reflect human values, but the preference data contains sensitive information, especially when derived from surveys about poli…
Safe at One Loop, Risky at Another: Aligning Safety Across Recurrent Depths in Looped Language Models
Yi Wang, Xiuyuan Qi, Dongqi Han +2
Looped Language Models (LoopLMs) provide a parameter efficient approach to scaling model capabilities through repeated use of shared parameters across recurrent steps. Since each r…
Recurrent Self-Improvement: Dynamic Cross-Loop On-Policy Distillation for Looped Language Models
Yi Wang, Rui Qian, Yu Li +2
Looped Language Models (LoopLMs) offer a parameter efficient approach to scaling reasoning by reusing shared parameters across recurrent computation steps. Despite their promise, e…
Evolving Paradigms in Task-Based Search and Learning: A Comparative Analysis of Traditional Search Engine with LLM-Enhanced Conversational Search System
Zhitong Guan, Yi Wang
Large Language Models (LLMs) are rapidly reshaping information retrieval by enabling interactive, generative, and inference-driven search. While traditional keyword-based search re…
SSFO: Self-Supervised Faithfulness Optimization for Retrieval-Augmented Generation
Xiaqiang Tang, Yi Wang, Keyu Hu +5
Retrieval-Augmented Generation (RAG) systems require Large Language Models (LLMs) to generate responses that are faithful to the retrieved context. However, faithfulness hallucinat…
From KMMLU-Redux to KMMLU-Pro: A Professional Korean Benchmark Suite for LLM Evaluation
Seokhee Hong, Sunkyoung Kim, Guijin Son +3
The development of Large Language Models (LLMs) requires robust benchmarks that encompass not only academic domains but also industrial fields to effectively evaluate their applica…
Assay2Mol: large language model-based drug design using BioAssay context
Yifan Deng, Spencer S. Ericksen, Anthony Gitter
Scientific databases aggregate vast amounts of quantitative data alongside descriptive text. In biochemistry, molecule screening assays evaluate candidate molecules' functional res…
PATS: Process-Level Adaptive Thinking Mode Switching
Yi Wang, Junxiao Liu, Shimao Zhang +2
Current large-language models (LLMs) typically adopt a fixed reasoning strategy, either simple or complex, for all questions, regardless of their difficulty. This neglect of variat…
RouteNator: A Router-Based Multi-Modal Architecture for Generating Synthetic Training Data for Function Calling LLMs
Vibha Belavadi, Tushar Vatsa, Dewang Sultania +5
This paper addresses fine-tuning Large Language Models (LLMs) for function calling tasks when real user interaction data is unavailable. In digital content creation tools, where us…
DELMAN: Dynamic Defense Against Large Language Model Jailbreaking with Model Editing
Yi Wang, Fenghua Weng, Sibei Yang +3
Large Language Models (LLMs) are widely applied in decision making, but their deployment is threatened by jailbreak attacks, where adversarial users manipulate model behavior to by…
DR.GAP: Mitigating Bias in Large Language Models using Gender-Aware Prompting with Decoupled Reasoning
Hongye Qiu, Yue Xu, Yi Wang +2
Large Language Models (LLMs) exhibit strong natural language understanding capabilities but also inherit and amplify societal biases, particularly gender bias, raising fairness con…
XTRUST: On the Multilingual Trustworthiness of Large Language Models
Yahan Li, Yi Wang, Yi Chang +1
Large language models (LLMs) have demonstrated remarkable capabilities across a range of natural language processing (NLP) tasks, capturing the attention of both practitioners and…
Recurrent Drafter for Fast Speculative Decoding in Large Language Models
Yunfei Cheng, Aonan Zhang, Xuanyu Zhang +2
We present Recurrent Drafter (ReDrafter), an advanced speculative decoding approach that achieves state-of-the-art speedup for large language models (LLMs) inference. The performan…