19 citations · 44 across the 19 of their papers we have counts for
9 papers · 1 filter
SCOPE: Optimizing Key-Value Cache Compression in Long-context Generation
Jialong Wu, Zhenglin Wang, Linhai Zhang +3
Key-Value (KV) cache has become a bottleneck of LLMs for long-context generation. Despite the numerous efforts in this area, the optimization for the decoding phase is generally ig…
A Comparative Study on Reasoning Patterns of OpenAI's o1 Model
Siwei Wu, Zhongyuan Peng, Xinrun Du +14
Enabling Large Language Models (LLMs) to handle a wider range of complex tasks (e.g., coding, math) has drawn great attention from many researchers. As LLMs continue to evolve, mer…
AdaCQR: Enhancing Query Reformulation for Conversational Search via Sparse and Dense Retrieval Alignment
Yilong Lai, Jialong Wu, Congzhi Zhang +2
Conversational Query Reformulation (CQR) has significantly advanced in addressing the challenges of conversational search, particularly those stemming from the latent user intent a…
Symbolic Learning Enables Self-Evolving Agents
Wangchunshu Zhou, Yixin Ou, Shengwei Ding +9
The AI community has been exploring a pathway to artificial general intelligence (AGI) by developing "language agents", which are complex large language models (LLMs) pipelines inv…
SEED: Accelerating Reasoning Tree Construction via Scheduled Speculative Decoding
Zhenglin Wang, Jialong Wu, Yilong Lai +2
Large Language Models (LLMs) demonstrate remarkable emergent abilities across various tasks, yet fall short of complex reasoning and planning tasks. The tree-search-based reasoning…
Causal Prompting: Debiasing Large Language Model Prompting based on Front-Door Adjustment
Congzhi Zhang, Linhai Zhang, Jialong Wu +2
Despite the notable advancements of existing prompting methods, such as In-Context Learning and Chain-of-Thought for Large Language Models (LLMs), they still face challenges relate…
DINER: Debiasing Aspect-based Sentiment Analysis with Multi-variable Causal Inference
Jialong Wu, Linhai Zhang, Deyu Zhou +1
Though notable progress has been made, neural-based aspect-based sentiment analysis (ABSA) models are prone to learn spurious correlations from annotation biases, resulting in poor…
STAR: Constraint LoRA with Dynamic Active Learning for Data-Efficient Fine-Tuning of Large Language Models
Linhai Zhang, Jialong Wu, Deyu Zhou +1
Though Large Language Models (LLMs) have demonstrated the powerful capabilities of few-shot learning through prompting methods, supervised training is still necessary for complex r…
Weaver: Foundation Models for Creative Writing
Tiannan Wang, Jiamin Chen, Qingrui Jia +43
This work introduces Weaver, our first family of large language models (LLMs) dedicated to content creation. Weaver is pre-trained on a carefully selected corpus that focuses on im…