Multimodal Retrieval Augmented Generation (MMRAG) is a powerful approach to questionanswering over multimodal documents. A key challenge with evaluating MMRAG is the paucity of high-quality datasets matching the question styles and modalities of interest. In light of this, we propose SMMQG, a synthetic data generation framework. SMMQG leverages interplay between a retriever, large language model (LLM) and large multimodal model (LMM) to generate question and answer pairs directly from multimodal documents, with the questions conforming to specified styles and modalities. We use SMMQG to generate an MMRAG dataset of 1024 questions Figure 1: An overview of SMMQG. Given userprovided over Wikipedia documents and evaluate stateof-the-art question style and modality requirements, SMmodels using it, revealing insights MQG selects question sources and produces questions into model performance that are attainable only and answers. The questions are grounded in the selected through style-and modality-specific evaluation question sources, and adhere to the question and modality data. Next, we measure the quality of data produced requirements.

Although great progress has been made by previous table understanding methods including recent approaches based on large language models (LLMs), they rely heavily on the premise that given tables must be converted into a certain text sequence (such as Markdown or HTML) to serve as model input. However, it is difficult to access such high-quality textual table representations in some real-world scenarios, and table images are much more accessible. Therefore, how to directly understand tables using intuitive visual information is a crucial and urgent challenge for developing more practical applications. In this paper, we propose a new problem, multimodal table understanding, where the model needs to generate correct responses to various table-related requests based on the given table image. To facilitate both the model training and evaluation, we construct a large-scale dataset named MMTab, which covers a wide spectrum of table images, instructions and tasks. On this basis, we develop Table-LLaVA, a generalist tabular multimodal large language model (MLLM), which significantly outperforms recent open-source MLLM baselines on 23 benchmarks under held-in and held-out settings. The code and data is available at this https://github.com/SpursGoZmy/Table-LLaVA

Thomas Haigh (thomas.haigh@gmail.com) is a professor of history at the University of Wisconsin--Milwaukee, WI, USA, and a Comenius visiting professor at Siegen University, Germany.

Social media users hurled criticism at Microsoft this week for what many thought was an AI-generated obituary for NBA player Brandon Hunter on its website MSN. The controversy began after the obituary -- which had a headline that read "Brandon Hunter useless at 42" written by "Editor" -- appeared on the Microsoft-owned platform after Hunter's death on Tuesday. The obituary goes on to refer to the former Boston Celtics and Orlando Magic player having been "handed away on the age of 42" and claimed he "performed in 67 video games over two seasons and achieved a career-high of 17 factors in a recreation in opposition to the Milwaukee Bucks in 2004." The post appeared to follow a similar format to a story on TMZ Sports, Futurism noted, "albeit with altered punctuation and a use of synonyms so liberal that the result is essentially incomprehensible." You can compare both the obituary containing the error and the TMZ Sports story here.

Former New Jersey Gov. Chris Christie tore into GOP presidential candidate Vivek Ramaswamy one day after the first primary debate in Milwaukee, arguing the entrepreneur's answers showed he has "absolutely no idea what he's talking about." Christie and Ramaswamy sparred over several issues during the two-hour debate from the United States' role in funding the war in Ukraine to supporting former President Donald Trump if he's convicted. Trump praised Ramaswamy's debate performance on his social media site Truth Social. Ramaswamy also praised Trump on stage as the "best president of the 21st century." "Well, I'm stunned that as I was talking about Donald Trump and all the ways that he's let down our party and our country, that he [Trump] didn't mention me as a winner of the debate last night," Christie said Thursday on "Your World."

On Wednesday night in Milwaukee, eight Republicans trailing Donald Trump in the 2024 presidential primary gathered for the cycle's first debate and, with a clear and united voice, denounced one man: Vivek Ramaswamy. With Trump running away with the race and Florida Gov. Ron DeSantis behind him in a clear (if tenuous) second, it was somehow the 38-year-old Ramaswamy who took the most direct hits. Former New Jersey Gov. Chris Christie's was likely the most memorable: After two of Ramaswamy's high-energy, relentlessly locquacious answers, Christie described him as "a guy who sounds like ChatGPT." Former vice president Mike Pence made a glaringly condescending reference to Ramaswamy "learning on the job," to which the crowd responded with a deserved oooooh. The Super PAC that supports DeSantis called Ramaswamy a fraud on Twitter, while you can see former South Carolina Gov. Nikki Haley's opinion of him expressed nonverbally above.

Thomas Haigh (thomas.haigh@gmail.com) is a professor of history at the University of Wisconsin--Milwaukee, WI, USA, and a Comenius visiting professor at Siegen University, Germany.

Former Wisconsin Gov. Scott Walker, R., joined Americas Newsroom to discuss what is at stake with the swing states pivotal election. A Wisconsin woman is using online dating applications to reach young people nationwide and help raise voter turnout during elections, according to a local report. Kristi Johnston is part of Next Gen. America, an organization that works toward increasing voter turnout among young Americans, WKOW-TV reported. Johnston and the group do not push for any specific political party or candidate and instead raise awareness and remind people to get out and vote.

Black widows must despise Clint Sergi. While working on his PhD in biology at the University of Wisconsin-Milwaukee, Sergi spent his time designing little challenges for spiders--which often involved rewarding them with tasty dead crickets, or confounding them by stealing the crickets away. "The big question that motivated the work was just wanting to know what is going on inside the minds of animals," he says. Biologists already know spider brains aren't like human brains. Their sensory world is geared for life in webs and dark corners.

MILWAUKEE -- Agriculture is among the last major industries to become digitized. It's doesn't come as a major surprise, seeing as how off-road, rural environments are more challenging than roadway systems or manufacturing floors. However, as the connectivity gap continues to close, there is tremendous opportunity to capture data that can ultimately lead to transformative technologies like artificial intelligence (AI). "To put it as simply as possible, AI allows computer systems to complete tasks that are normally performed by humans," said Mark Kuehn, OEM sales manager for North America at Trimble. Given that definition, AI could mean everything from cognitive tasks like data analytics and forecasting to physical tasks like spraying weeds and picking produce.