3 citations · 5 across the 9 of their papers we have counts for
9 papers · 1 filter
Can LLMs Access their World Knowledge for Event Prediction?
Zijun Wu, Zhitian Zhang, Hossein Hajimirsadeghi +2
Recent work has questioned whether large language models (LLMs) can be useful for temporal event prediction. Despite vast pretrained world knowledge, LLMs often underperform simple…
Multi-Persona Thinking for Bias Mitigation in Large Language Models
Yuxing Chen, Guoqing Luo, Zijun Wu +1
Large Language Models (LLMs) exhibit social biases, which can lead to harmful stereotypes and unfair outcomes. We propose \textbf{Multi-Persona Thinking (MPT)}, a simple inference-…
TokMem: One-Token Procedural Memory for Large Language Models
Zijun Wu, Yongchang Hao, Lili Mou
Large language models are typically controlled via prompts, which must be repeatedly re-processed for every new query and are difficult to reuse modularly. We introduce TokMem, a p…
Ultra-Low-Dimensional Prompt Tuning via Random Projection
Zijun Wu, Yongchang Hao, Lili Mou
Large language models achieve state-of-the-art performance but are increasingly costly to fine-tune. Prompt tuning is a parameter-efficient fine-tuning method that addresses parame…
Cross-Modal Consistency in Multimodal Large Language Models
Xiang Zhang, Senyu Li, Ning Shi +5
Recent developments in multimodal methodologies have marked the beginning of an exciting era for models adept at processing diverse data types, encompassing text, audio, and visual…
Reducing Distraction in Long-Context Language Models by Focused Learning
Zijun Wu, Bingyuan Liu, Ran Yan +2
Recent advancements in Large Language Models (LLMs) have significantly enhanced their capacity to process long contexts. However, effectively utilizing this long context remains a…
Action Controlled Paraphrasing
Ning Shi, Zijun Wu
Recent studies have demonstrated the potential to control paraphrase generation, such as through syntax, which has broad applications in various downstream tasks. However, these me…
Zero-Shot Continuous Prompt Transfer: Generalizing Task Semantics Across Language Models
Zijun Wu, Yongkang Wu, Lili Mou
Prompt tuning in natural language processing (NLP) has become an increasingly popular method for adapting large language models to specific tasks. However, the transferability of t…
The Emergence of Chunking Structures with Hierarchical RNN
Zijun Wu, Anup Anand Deshmukh, Yongkang Wu +2
In Natural Language Processing (NLP), predicting linguistic structures, such as parsing and chunking, has mostly relied on manual annotations of syntactic structures. This paper in…