16 citations · 33 across the 15 of their papers we have counts for
15 papers
On the Efficiency-Safety Dilemma in Large Reasoning Models
Yifei Yang, Zouying Cao, Xingrui Wang +4
Large reasoning models (LRMs) incur high inference costs, often mitigated by efficiency techniques like quantization and pruning. However, the impact of these techniques on model a…
PGPO: Enhancing Agent Reasoning via Pseudocode-style Planning Guided Preference Optimization
Zouying Cao, Runze Wang, Yifei Yang +4
Large Language Model (LLM) agents have demonstrated impressive capabilities in handling complex interactive problems. Existing LLM agents mainly generate natural language plans to…
How Deep is Love in LLMs' Hearts? Exploring Semantic Size in Human-like Cognition
Yao Yao, Yifei Yang, Xinbei Ma +4
How human cognitive abilities are formed has long captivated researchers. However, a significant challenge lies in developing meaningful methods to measure these complex processes.…
LESA: Learnable LLM Layer Scaling-Up
Yifei Yang, Zouying Cao, Xinbei Ma +4
Training Large Language Models (LLMs) from scratch requires immense computational resources, making it prohibitively expensive. Model scaling-up offers a promising solution by leve…
KVSharer: Efficient Inference via Layer-Wise Dissimilar KV Cache Sharing
Yifei Yang, Zouying Cao, Qiguang Chen +4
The development of large language models (LLMs) has significantly expanded model sizes, resulting in substantial GPU memory requirements during inference. The key and value storage…
SCANS: Mitigating the Exaggerated Safety for LLMs via Safety-Conscious Activation Steering
Zouying Cao, Yifei Yang, Hai Zhao
Safety alignment is indispensable for Large Language Models (LLMs) to defend threats from malicious instructions. However, recent researches reveal safety-aligned LLMs prone to rej…
Hypertext Entity Extraction in Webpage
Yifei Yang, Tianqiao Liu, Bo Shao +4
Webpage entity extraction is a fundamental natural language processing task in both research and applications. Nowadays, the majority of webpage entity extraction models are traine…
Head-wise Shareable Attention for Large Language Models
Zouying Cao, Yifei Yang, Hai Zhao
Large Language Models (LLMs) suffer from huge number of parameters, which restricts their deployment on edge devices. Weight sharing is one promising solution that encourages weigh…
LaCo: Large Language Model Pruning via Layer Collapse
Yifei Yang, Zouying Cao, Hai Zhao
Large language models (LLMs) based on transformer are witnessing a notable trend of size expansion, which brings considerable costs to both model training and inference. However, e…
AutoHall: Automated Factuality Hallucination Dataset Generation for Large Language Models
Zouying Cao, Yifei Yang, XiaoJing Li +1
Large language models (LLMs) have gained broad applications across various domains but still struggle with hallucinations. Currently, hallucinations occur frequently in the generat…
BatGPT: A Bidirectional Autoregessive Talker from Generative Pre-trained Transformer
Zuchao Li, Shitou Zhang, Hai Zhao +2
BatGPT is a large-scale language model designed and trained jointly by Wuhan University and Shanghai Jiao Tong University. It is capable of generating highly natural and fluent tex…
CMMLU: Measuring massive multitask language understanding in Chinese
Haonan Li, Yixuan Zhang, Fajri Koto +5
As the capabilities of large language models (LLMs) continue to advance, evaluating their performance becomes increasingly crucial and challenging. This paper aims to bridge this g…
Attack Named Entity Recognition by Entity Boundary Interference
Yifei Yang, Hongqiu Wu, Hai Zhao
Named Entity Recognition (NER) is a cornerstone NLP task while its robustness has been given little attention. This paper rethinks the principles of NER attacks derived from senten…
RefGPT: Dialogue Generation of GPT, by GPT, and for GPT
Dongjie Yang, Ruifeng Yuan, Yuantao Fan +4
Large Language Models (LLMs) have attained the impressive capability to resolve a wide range of NLP tasks by fine-tuning high-quality instruction data. However, collecting human-wr…
Nested Named Entity Recognition as Holistic Structure Parsing
Yifei Yang, Zuchao Li, Hai Zhao
As a fundamental natural language processing task and one of core knowledge extraction techniques, named entity recognition (NER) is widely used to extract information from texts f…