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Related papers: Do Large Language Models Know How Much They Know?

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An essential problem in artificial intelligence is whether LLMs can simulate human cognition or merely imitate surface-level behaviors, while existing datasets suffer from either synthetic reasoning traces or population-level aggregation,…

Computation and Language · Computer Science 2026-03-31 Yuxuan Gu , Lunjun Liu , Xiaocheng Feng , Kun Zhu , Weihong Zhong , Lei Huang , Bing Qin

Large language models (LLMs) are complex artificial intelligence systems capable of understanding, generating and translating human language. They learn language patterns by analyzing large amounts of text data, allowing them to perform…

Cryptography and Security · Computer Science 2024-03-15 Biwei Yan , Kun Li , Minghui Xu , Yueyan Dong , Yue Zhang , Zhaochun Ren , Xiuzhen Cheng

Knowledge is fundamental to the overall capabilities of Large Language Models (LLMs). The knowledge paradigm of a model, which dictates how it encodes and utilizes knowledge, significantly affects its performance. Despite the continuous…

Computation and Language · Computer Science 2025-04-10 Xiaotian Ye , Mengqi Zhang , Shu Wu

Large Language Models (LLMs) as chatbots have drawn remarkable attention thanks to their versatile capability in natural language processing as well as in a wide range of tasks. While there has been great enthusiasm towards adopting such…

Systems and Control · Electrical Eng. & Systems 2024-06-24 Subir Majumder , Lin Dong , Fatemeh Doudi , Yuting Cai , Chao Tian , Dileep Kalathi , Kevin Ding , Anupam A. Thatte , Na Li , Le Xie

The capabilities of large language models (LLMs) have expanded beyond natural language processing to scientific prediction tasks, including molecular property prediction. However, their effectiveness in in-context learning remains…

Large language models (LLMs) have advanced rapidly, emerging as versatile tools across fields thanks to their exceptional language understanding, generation, and reasoning capabilities. However, performing LLM inference at the network edge…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-04-28 Zhixiong Chen , Bingjie Zhu , Jiangzhou Wang , Hyundong Shin , Arumugam Nallanathan , Dusit Niyato

Service robots need common-sense knowledge to help humans in everyday situations as it enables them to understand the context of their actions. However, approaches that use ontologies face a challenge because common-sense knowledge is often…

Robotics · Computer Science 2023-11-16 Felix Ocker , Jörg Deigmöller , Julian Eggert

Large language models (LLMs) often necessitate extensive labeled datasets and training compute to achieve impressive performance across downstream tasks. This paper explores a self-training paradigm, where the LLM autonomously curates its…

Computation and Language · Computer Science 2024-11-13 Wei Jie Yeo , Teddy Ferdinan , Przemyslaw Kazienko , Ranjan Satapathy , Erik Cambria

Large Language Models (LLMs) have quickly risen to prominence due to their ability to perform at or close to the state-of-the-art in a variety of fields while handling natural language. An important field of research is the application of…

Cryptography and Security · Computer Science 2024-02-28 Gabriel de Jesus Coelho da Silva , Carlos Becker Westphall

This work presents a framework for assessing whether large language models (LLMs) encode more factual knowledge in their parameters than what they express in their outputs. While a few studies hint at this possibility, none has clearly…

Computation and Language · Computer Science 2025-08-07 Zorik Gekhman , Eyal Ben David , Hadas Orgad , Eran Ofek , Yonatan Belinkov , Idan Szpektor , Jonathan Herzig , Roi Reichart

Large Language Models (LLMs) show great promise as a powerful tool for scientific literature exploration. However, their effectiveness in providing scientifically accurate and comprehensive answers to complex questions within specialized…

Modern language models (LMs) pose a new challenge in capability assessment. Static benchmarks inevitably saturate without providing confidence in the deployment tolerances of LM-based systems, but developers nonetheless claim that their…

Software Engineering · Computer Science 2024-07-31 Michael Saxon , Ari Holtzman , Peter West , William Yang Wang , Naomi Saphra

Large Language Models (LLMs) have been transformative. They are pre-trained foundational models that are self-supervised and can be adapted with fine tuning to a wide range of natural language tasks, each of which previously would have…

Computation and Language · Computer Science 2023-02-22 Terrence Sejnowski

Large Language Models (LLMs) are frequently utilized as sources of knowledge for question-answering. While it is known that LLMs may lack access to real-time data or newer data produced after the model's cutoff date, it is less clear how…

Computation and Language · Computer Science 2025-07-30 Agam Shah , Liqin Ye , Sebastian Jaskowski , Wei Xu , Sudheer Chava

As large language models (LLMs) continue to advance, there is a growing urgency to enhance the interpretability of their internal knowledge mechanisms. Consequently, many interpretation methods have emerged, aiming to unravel the knowledge…

Computation and Language · Computer Science 2025-06-11 Jiaxiang Liu , Boxuan Xing , Chenhao Yuan , Chenxiang Zhang , Di Wu , Xiusheng Huang , Haida Yu , Chuhan Lang , Pengfei Cao , Jun Zhao , Kang Liu

Inspired by the exceptional general intelligence of Large Language Models (LLMs), researchers have begun to explore their application in pioneering the next generation of recommender systems - systems that are conversational, explainable,…

Information Retrieval · Computer Science 2024-08-06 Wensheng Lu , Jianxun Lian , Wei Zhang , Guanghua Li , Mingyang Zhou , Hao Liao , Xing Xie

The rapid development of Large Language Models (LLMs) demonstrates remarkable multilingual capabilities in natural language processing, attracting global attention in both academia and industry. To mitigate potential discrimination and…

Computation and Language · Computer Science 2025-01-08 Kaiyu Huang , Fengran Mo , Xinyu Zhang , Hongliang Li , You Li , Yuanchi Zhang , Weijian Yi , Yulong Mao , Jinchen Liu , Yuzhuang Xu , Jinan Xu , Jian-Yun Nie , Yang Liu

Large Language Models (LLMs) have demonstrated amazing capabilities in language generation, text comprehension, and knowledge reasoning. While a single powerful model can already handle multiple tasks, relying on a single perspective can…

Computation and Language · Computer Science 2024-06-12 Zining Qin , Chenhao Wang , Huiling Qin , Weijia Jia

Large language models (LLMs) have shown impressive capabilities across tasks such as mathematics, coding, and reasoning, yet their learning ability, which is crucial for adapting to dynamic environments and acquiring new knowledge, remains…

Computation and Language · Computer Science 2025-12-29 Zhengyu Hu , Jianxun Lian , Zheyuan Xiao , Seraphina Zhang , Tianfu Wang , Nicholas Jing Yuan , Xing Xie , Hui Xiong

Large Language Models (LLMs) such as ChatGPT demonstrated the potential to replicate human language abilities through technology, ranging from text generation to engaging in conversations. However, it remains controversial to what extent…

Computation and Language · Computer Science 2025-07-09 Martin Schuele