Foundational challenges in assuring alignment and safety of large language models

U Anwar, A Saparov, J Rando, D Paleka… - arxiv preprint arxiv …, 2024 - arxiv.org
This work identifies 18 foundational challenges in assuring the alignment and safety of large
language models (LLMs). These challenges are organized into three different categories …

Crowds can effectively identify misinformation at scale

C Martel, J Allen, G Pennycook… - Perspectives on …, 2024 - journals.sagepub.com
Identifying successful approaches for reducing the belief and spread of online
misinformation is of great importance. Social media companies currently rely largely on …

Reinforcement learning-based counter-misinformation response generation: a case study of COVID-19 vaccine misinformation

B He, M Ahamad, S Kumar - Proceedings of the ACM Web Conference …, 2023 - dl.acm.org
The spread of online misinformation threatens public health, democracy, and the broader
society. While professional fact-checkers form the first line of defense by fact-checking …

Factcheck-bench: Fine-grained evaluation benchmark for automatic fact-checkers

Y Wang, RG Reddy, Z Mujahid, A Arora… - Findings of the …, 2024 - aclanthology.org
The increased use of large language models (LLMs) across a variety of real-world
applications calls for mechanisms to verify the factual accuracy of their outputs. In this work …

Moral emotions shape the virality of COVID-19 misinformation on social media

K Solovev, N Pröllochs - Proceedings of the ACM web conference 2022, 2022 - dl.acm.org
While false rumors pose a threat to the successful overcoming of the COVID-19 pandemic,
an understanding of how rumors diffuse in online social networks is–even for non-crisis …

Factcheck-GPT: End-to-End Fine-Grained Document-Level Fact-Checking and Correction of LLM Output

Y Wang, RG Reddy, ZM Mujahid, A Arora… - arxiv preprint arxiv …, 2023 - arxiv.org
The increased use of large language models (LLMs) across a variety of real-world
applications calls for mechanisms to verify the factual accuracy of their outputs. In this work …

The effects of crowd worker biases in fact-checking tasks

T Draws, D La Barbera, M Soprano, K Roitero… - Proceedings of the …, 2022 - dl.acm.org
Due to the increasing amount of information shared online every day, the need for sound
and reliable ways of distinguishing between trustworthy and non-trustworthy information is …

Birdwatch: Crowd wisdom and bridging algorithms can inform understanding and reduce the spread of misinformation

S Wojcik, S Hilgard, N Judd, D Mocanu… - arxiv preprint arxiv …, 2022 - arxiv.org
We present an approach for selecting objectively informative and subjectively helpful
annotations to social media posts. We draw on data from on an online environment where …

Should we agree to disagree about Twitter's bot problem?

O Varol - Online Social Networks and Media, 2023 - Elsevier
Bots, simply defined as accounts controlled by automation, can be used as a weapon for
online manipulation and pose a threat to the health of platforms. Researchers have studied …

[HTML][HTML] Considering information-sharing motives to reduce misinformation

L Globig, T Sharot - Current Opinion in Psychology, 2024 - Elsevier
Misinformation has risen in recent years, negatively effecting domains ranging from politics
to health. To curb the spread of misinformation it is useful to consider why, how, and when …