7 papers
HPRO: Hierarchical Progressive Reward Optimization via Preference Extraction for Emotional Text-to-Speech
Sihang Nie, Xiaofen Xing, Rui Xing +5
Recently, Large Language Model (LLM)-based Text-to-Speech (TTS) models have achieved remarkable naturalness. However, the standard Supervised Fine-Tuning paradigm often converges t…
VCT: A Verifiable Transcript System for LLM Conversations
Ruilin Xing, Feihong Li, Jiayue Liu +3
Large language model (LLM) interaction records are increasingly vital in digital forensics and compliance auditing. However, traditional linear tamper-evident logs fail to capture…
FinChain: A Symbolic Benchmark for Verifiable Chain-of-Thought Financial Reasoning
Zhuohan Xie, Daniil Orel, Rushil Thareja +22
Multi-step symbolic reasoning is essential for robust financial analysis; yet, current benchmarks largely overlook this capability. Existing datasets such as FinQA and ConvFinQA em…
Is Human-Like Text Liked by Humans? Multilingual Human Detection and Preference Against AI
Yuxia Wang, Rui Xing, Jonibek Mansurov +23
Prior studies have shown that distinguishing text generated by Large Language Models (LLMs) from human-written one is highly challenging for humans, and often no better than random…
AI Security Beyond Core Domains: Resume Screening as a Case Study of Adversarial Vulnerabilities in Specialized LLM Applications
Honglin Mu, Jinghao Liu, Kaiyang Wan +4
Large Language Models (LLMs) excel at text comprehension and generation, making them ideal for automated tasks like code review and content moderation. However, our research identi…
Unconditional Truthfulness: Learning Unconditional Uncertainty of Large Language Models
Artem Vazhentsev, Ekaterina Fadeeva, Rui Xing +7
Uncertainty quantification (UQ) has emerged as a promising approach for detecting hallucinations and low-quality output of Large Language Models (LLMs). However, obtaining proper u…