8 citations · 8 across the 8 of their papers we have counts for
9 papers
SpanUQ: Span-Level Uncertainty Quantification for Large Language Model Generation
Yimeng Zhang, Yingying Zhuang, Ziyi Wang +12
Uncertainty estimation is essential for the trustworthy deployment of LLMs: it underpins self-refinement and serves as a decision signal for downstream systems, from verifiers to c…
Multimodal Foundation Model-Driven User Interest Modeling and Behavior Analysis on Short Video Platforms
Yushang Zhao, Yike Peng, Li Zhang +3
With the rapid expansion of user bases on short video platforms, personalized recommendation systems are playing an increasingly critical role in enhancing user experience and opti…
ParlAI Vote: A Web Platform for Analyzing Gender and Political Bias in Large Language Models
Wenjie Lin, Hange Liu, Yingying Zhuang +5
We present ParlAI Vote, an interactive web platform for exploring European Parliament debates and votes, and for testing LLMs on vote prediction and bias analysis. This web system…
How and Where to Translate? The Impact of Translation Strategies in Cross-lingual LLM Prompting
Aman Gupta, Yingying Zhuang, Zhou Yu +2
Despite advances in the multilingual capabilities of Large Language Models (LLMs), their performance varies substantially across different languages and tasks. In multilingual retr…
Multilingual Information Retrieval with a Monolingual Knowledge Base
Yingying Zhuang, Aman Gupta, Anurag Beniwal
Multilingual information retrieval has emerged as powerful tools for expanding knowledge sharing across languages. On the other hand, resources on high quality knowledge base are o…
REIC: RAG-Enhanced Intent Classification at Scale
Ziji Zhang, Michael Yang, Zhiyu Chen +6
Accurate intent classification is critical for efficient routing in customer service, ensuring customers are connected with the most suitable agents while reducing handling times a…
When Thinking Fails: The Pitfalls of Reasoning for Instruction-Following in LLMs
Xiaomin Li, Zhou Yu, Zhiwei Zhang +5
Reasoning-enhanced large language models (RLLMs), whether explicitly trained for reasoning or prompted via chain-of-thought (CoT), have achieved state-of-the-art performance on man…
Semantic Volume: Quantifying and Detecting both External and Internal Uncertainty in LLMs
Xiaomin Li, Zhou Yu, Ziji Zhang +4
Large language models (LLMs) have demonstrated remarkable performance across diverse tasks by encoding vast amounts of factual knowledge. However, they are still prone to hallucina…
DualVD: An Adaptive Dual Encoding Model for Deep Visual Understanding in Visual Dialogue
Xiaoze Jiang, Jing Yu, Zengchang Qin +4
Different from Visual Question Answering task that requires to answer only one question about an image, Visual Dialogue involves multiple questions which cover a broad range of vis…