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相关论文: SycEval: Evaluating LLM Sycophancy

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Large language models (LLMs) have become mainstream technology with their versatile use cases and impressive performance. Despite the countless out-of-the-box applications, LLMs are still not reliable. A lot of work is being done to improve…

计算与语言 · 计算机科学 2023-06-13 Aisha Khatun , Daniel G. Brown

While Large Language Models (LLMs) are widely documented to be sensitive to minor prompt perturbations and prone to sycophantic alignment, their robustness in consequential, rule-bound decision-making remains under-explored. We uncover a…

人工智能 · 计算机科学 2026-04-07 Jon Chun , Katherine Elkins

The dream of achieving a student-teacher ratio of 1:1 is closer than ever thanks to the emergence of large language models (LLMs). One potential application of these models in the educational field would be to provide feedback to students…

计算机与社会 · 计算机科学 2025-05-06 Marc Ballestero-Ribó , Daniel Ortiz-Martínez

Providing scaffolding through educational chatbots built on Large Language Models (LLM) has potential risks and benefits that remain an open area of research. When students navigate impasses, they ask for help by formulating impasse-driven…

人机交互 · 计算机科学 2026-02-23 Alexandra Neagu , Marcus Messer , Peter Johnson , Rhodri Nelson

Large Language Models (LLMs) demonstrate increasingly human-like abilities across a wide variety of tasks. In this paper, we investigate whether LLMs like ChatGPT can accurately infer the psychological dispositions of social media users and…

计算与语言 · 计算机科学 2024-06-06 Heinrich Peters , Sandra Matz

Integration of Large Language Models with search/retrieval engines has become ubiquitous, yet these systems harbor a critical vulnerability that undermines their reliability. We present the first systematic investigation of "chameleon…

计算与语言 · 计算机科学 2025-10-28 Shivam Ratnakar , Sanjay Raghavendra

A growing body of research assumes that large language model (LLM) agents can serve as proxies for how people form attitudes toward and behave in response to security and privacy (S&P) threats. If correct, these simulations could offer a…

计算机与社会 · 计算机科学 2026-02-25 Yuxuan Li , Leyang Li , Hao-Ping Lee , Sauvik Das

As large language models (LLMs) are increasingly deployed in sensitive everyday contexts -- offering personal advice, mental health support, and moral guidance -- understanding their behavior in navigating complex moral reasoning is…

人工智能 · 计算机科学 2026-03-10 Pratik S. Sachdeva , Tom van Nuenen

Large Language Models (LLMs) like ChatGPT, DeepSeek and Gemini seem to be increasingly used for knowledge discovery, information retrieval, and knowledge summaries, including for academic topics. This can result in users being misled, such…

信息检索 · 计算机科学 2026-05-28 Mike Thelwall

As large language models (LLMs) have been deployed in various real-world settings, concerns about the harm they may propagate have grown. Various jailbreaking techniques have been developed to expose the vulnerabilities of these models and…

计算与语言 · 计算机科学 2025-02-19 Yubin Ge , Neeraja Kirtane , Hao Peng , Dilek Hakkani-Tür

There are growing promises that Large Language Models (LLMs) can support students' learning by providing explanations, feedback, and guidance. However, despite their rapid adoption and widespread attention, there is still limited empirical…

We investigate the presence of cognitive biases in three large language models (LLMs): GPT-4o, Gemma 2, and Llama 3.1. The study uses 1,500 experiments across nine established cognitive biases to evaluate the models' responses and…

人工智能 · 计算机科学 2025-09-11 Payam Saeedi , Mahsa Goodarzi , M Abdullah Canbaz

Large language models (LLMs) implicitly learn to perform a range of language tasks, including machine translation (MT). Previous studies explore aspects of LLMs' MT capabilities. However, there exist a wide variety of languages for which…

计算与语言 · 计算机科学 2023-09-15 Nathaniel R. Robinson , Perez Ogayo , David R. Mortensen , Graham Neubig

This study investigates the potential of a multimodal large language model (LLM), specifically ChatGPT-4o, to perform human-like interpretations of traffic scenes using static dashcam images. Herein, we focus on three judgment tasks…

计算机视觉与模式识别 · 计算机科学 2025-07-14 Yuki Yoshihara , Linjing Jiang , Nihan Karatas , Hitoshi Kanamori , Asuka Harada , Takahiro Tanaka

With LLM usage becoming widespread across countries, languages, and humanity more broadly, the need to understand and guardrail their multilingual responses increases. Large-scale datasets for testing and benchmarking have been created to…

计算与语言 · 计算机科学 2025-10-13 Kimaya Basu , Savi Kolari , Allison Yu

Rapid improvements in large language models have unveiled a critical challenge in human-AI interaction: sycophancy. In this context, sycophancy refers to the tendency of models to excessively agree with or flatter users, often at the…

计算与语言 · 计算机科学 2025-03-18 Joshua Liu , Aarav Jain , Soham Takuri , Srihan Vege , Aslihan Akalin , Kevin Zhu , Sean O'Brien , Vasu Sharma

Large Language Models (LLMs) are increasingly applied to automate software engineering tasks, including the generation of UML class diagrams from natural language descriptions. While prior work demonstrates that LLMs can produce…

软件工程 · 计算机科学 2026-04-07 Rabia Iftikhar , Andreas Rausch

As ChatGPT and GPT-4 spearhead the development of Large Language Models (LLMs), more researchers are investigating their performance across various tasks. But more research needs to be done on the interpretability capabilities of LLMs, that…

计算与语言 · 计算机科学 2023-10-27 Dongfang Li , Jindi Yu , Baotian Hu , Zhenran Xu , Min Zhang

The use of large language model (LLM)-powered chatbots, such as ChatGPT, has become popular across various domains, supporting a range of tasks and processes. However, due to the intrinsic complexity of LLMs, effective prompting is more…

When making decisions under uncertainty, individuals often deviate from rational behavior, which can be evaluated across three dimensions: risk preference, probability weighting, and loss aversion. Given the widespread use of large language…

人工智能 · 计算机科学 2024-11-04 Jingru Jia , Zehua Yuan , Junhao Pan , Paul E. McNamara , Deming Chen
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