Large Language Models (LLMs) have fundamentally reshaped Argument Mining (AM), shifting it from a pipeline of supervised, task-specific classifiers to a spectrum of prompt-driven, retrieval-augmented, and reasoning-oriented paradigms. Yet existing surveys largely predate this transition, leaving unclear how LLMs alter task formulations, dataset design, evaluation methodology, and the theoretical foundations of computational argumentation. In this survey, we synthesise research and provide the first unified account of AM in the LLM era. We revisit canonical AM subtasks, i.e., claim and evidence detection, relation prediction, stance classification, argument quality assessment, and argumentative summarisation, and show how prompting, chain-of-thought reasoning, and in-context learning blur traditional task boundaries. We catalogue the rapid evolution of resources, including integrated multi-layer corpora and LLM-assisted annotation pipelines that introduce new opportunities as well as risks of bias and evaluation circularity. Building on this mapping, we identify emerging architectural patterns across LLM-based AM systems and consolidate evaluation practices spanning component-level accuracy, soft-label quality assessment, and LLM-judge reliability. Finally, we outline persistent challenges, including long-context reasoning, multimodal and multilingual robustness, interpretability, and cost-efficient deployment, and propose a forward-looking research agenda for LLM-driven computational argumentation.

Stand aside, Siri and Alexa. An IBM team led by artificial intelligence (A.I.) researcher Noam Slonim has devised a system that does not merely answer questions; it debates the questioners. In a contest against champion human debaters, Slonim's Project Debater, which speaks with a female voice, impressed the judges. She didn't win, but that could change. As her developers explain in a March Nature article, Project Debater's computational argumentation technology consists of four main modules.

In February, 2011, an Israeli computer scientist named Noam Slonim proposed building a machine that would be better than people at something that seems inextricably human: arguing about politics. Slonim, who had done his doctoral work on machine learning, works at an I.B.M. Research facility in Tel Aviv, and he had watched with pride a few days before as the company's natural-language-processing machine, Watson, won "Jeopardy!" Afterward, I.B.M. sent an e-mail to thousands of researchers across its global network of labs, soliciting ideas for a "grand challenge" to follow the "Jeopardy!" It occurred to Slonim that they might try to build a machine that could defeat a champion debater. He made a single-slide presentation, and then a somewhat more elaborate one, and then a more elaborate one still, and, after many rounds competing against many other I.B.M. researchers, Slonim won the chance to build his machine, which he called Project Debater.

Today on the Science Talk podcast, Noam Slonim of IBM Research speaks to Scientific American about an impressive feat of computer engineering: an AI-powered autonomous system that can engage in complex debate with humans over issues ranging from subsidizing preschool and the merit of space exploration to the pros and cons of genetic engineering. In a new Nature paper, Slonim and his colleagues show that across 80 debate topics, Project Debater's computational argument technology has performed very decently--with a human audience being the judge of that. "However, it is still somewhat inferior on average to the results obtained by expert human debaters," Slonim says. In a 2019 San Francisco showcase, the system went head-to-head with expert debater Harish Natarajan. Beyond gaming, it's rare to see humans and machines go against each other, let alone in an oratory competition.

AI has the potential to power driverless cars and smart cities. But critics say the technology could perpetuate bias, put people out of work and even threaten human existence. About 500 university students attended Thursday's debate, hinting at just how controversial the technology is. The IBM machine, which was defeated by a human in a one-on-one debate nine months ago, delivered each team's 4-minute opening speech using submissions sourced ahead of time from over 1,000 people. The rebuttals by each side were done by the human debaters, who also delivered the closing arguments.

The Healthy Nevada Project, developed by Renown Institute for Health Innovation (Renown IHI), is one of the first community-based population health studies in the United States. By combining genetic data, environmental data and individual health information, researchers and physicians are gaining new insight into population health, enabling personalized health care while improving the health and well-being of entire communities in Nevada. The Project comes at a time when the state continues to struggle with poor health outcomes and excess costs. Nevada ranks near the bottom of overall health rankings in the U.S. and suffers from high mortality rates for chronic conditions like heart disease, cancer and chronic respiratory disease. "This was our call to action," says Dr. Anthony Slonim, President and CEO of Renown Health.

Champion debater Harish Natarajan argues against IBM Debater, represented by a screen with a blue oval, in a competition at the IBM Think conference. Champion debater Harish Natarajan argues against IBM Debater, represented by a screen with a blue oval, in a competition at the IBM Think conference. Champion debater Harish Natarajan argues against IBM Debater, represented by a screen with a blue oval, in a competition at the IBM Think conference. Champion debater Harish Natarajan argues against IBM Debater, represented by a screen with a blue oval, in a competition at the IBM Think conference. IBM fell short in its latest attempt to prove machines can triumph over man.

Alan Turing, one of the founders of modern computing, posited (In "Computing Machinery and Intelligence") holding a conversation with a computer and not being able to distinguish that conversation from one with a human. One of the main goals of artificial intelligence (AI) is to pass that test. IBM Research recently announced an intriguing step towards passing the Turing test. Project Debater is an attempt to have a real-time debate with a human. The team is led by IBM's research lab in Haifa, Israel, and the result was a short debate that included four minute opening statements and four minute rebuttals by both Project Debater and Noa Ovadia, the 2016 Israel national debate champion.

I've been told it helps to take a deep breath. But unfortunately, I cannot do that." The setting is a competitive debate being held at Watson West, IBM's AI outpost in San Francisco's tech-centric SOMA neighborhood. Noa is Noa Ovadia, a champion debater from Israel. The speaker greeting her is her opponent--whose inability to breathe deeply makes perfect sense given that it's a piece of software, generating Siri-like female speech that emanates from a human-sized black column with a screen on its front. This is indeed the first time that the software in question, Project Debater, has shown its stuff outside of secret trial runs. Since 2012, IBM Research has been teaching it to debate humans on a vast array of subjects--making it a successor to Deep Blue (which beat Garry Kasparov in a six-game chess match in 1997) and Watson (which won a Jeopardy tournament against Ken Jennings and Brad Rutter in 2011). That was good enough to make the exhibition a success in the eyes of Noam Slonim, a senior technical staff member at IBM's research center in Haifa, Israel and the person who originally proposed the Project Debater idea in 2011. The effort now includes dozens of researchers at multiple IBM labs and is led by Slonim's Haifa colleague Ranit Aharonov. Merely seeing the software keep the audience engaged over a 20-minute debate "was a very positive feeling," he tells me at a post-debate reception. Witnessing a computer thrash the Kasparovs and Jenningses of competitive debating at their own craft would be an epoch-shifting moment, but "our goal is not to develop yet another system that is better than humans in doing something," stresses Aharonov. Instead, IBM wants to create debating software that can spar with "a reasonably competent human, but not necessarily a world champion, and come across holding its own," says IBM director of research Arvind Krishna. Still, even if the company is keeping its aspirations in check, its latest adventure in AI involves challenges unlike any it's tackled before. Soon after Watson bested Jennings and Rutter in a tournament taped at IBM's Yorktown, N.Y. research center in January 2011, the company began to think about how to top that memorable feat of artificial intelligence. "All of the thousands of researchers … got the same email asking what should be the next AI grand challenge that IBM Research should pursue," remembers Slonim. The goal, he explains, was to come up with a project that was "scientifically interesting and challenging and would have some business value.

In what may be the biggest rollout of conversational AI from IBM since Watson, IBM Research today debuted Project Debater, an experimental conversational AI with a sense of humor, little tact, and occasionally powerful arguments. Training of Project Debater began six years ago, but it only gained an ability to participate in debates with people two years ago, said Noam Slonim, IBM Research principal investigator and creator of Project Debater. Debater's smarts come from hundreds of millions of interactions with millions of journal and newspaper articles. The AI system's ability to deliver persuasive arguments was demonstrated for an audience of tech journalists gathered at IBM offices in San Francisco, where the AI system participated in debates about whether governments should subsidize space exploration and whether telemedicine should play a bigger role in health care. When Project Debater gets a new topic, it searches its corpus of articles for sentences and clauses that are relevant, argumentative, and support its side of the debate.