Conversational recommender systems (CRS) enable users to articulate their preferences and provide feedback through natural language. With the advent of large language models (LLMs), the potential to enhance user engagement with CRS and augment the recommendation process with LLM-generated content has received increasing attention. However, the efficacy of LLM-powered CRS is contingent upon the use of prompts, and the subjective perception of recommendation quality can differ across various recommendation domains. Therefore, we have developed a ChatGPT-based CRS to investigate the impact of these two factors, prompt guidance (PG) and recommendation domain (RD), on the overall user experience of the system. We conducted an online empirical study (N = 100) by employing a mixed-method approach that utilized a between-subjects design for the variable of PG (with vs. without) and a within-subjects design for RD (book recommendations vs. job recommendations). The findings reveal that PG can substantially enhance the system's explainability, adaptability, perceived ease of use, and transparency. Moreover, users are inclined to perceive a greater sense of novelty and demonstrate a higher propensity to engage with and try recommended items in the context of book recommendations as opposed to job recommendations. Furthermore, the influence of PG on certain user experience metrics and interactive behaviors appears to be modulated by the recommendation domain, as evidenced by the interaction effects between the two examined factors. This work contributes to the user-centered evaluation of ChatGPT-based CRS by investigating two prominent factors and offers practical design guidance.

Yet this month, it antagonized someone much more powerful, and is already retreating just a touch. On Monday evening, Scarlett Johansson issued a statement to NPR's Bobby Allyn about OpenAI's GPT-4o announcement, which the company showcased in a live demonstration just last week. Specifically, the multimodal computer interaction model centered around a voice assistant named Sky, whose timbre really, really resembled ScarJo's. "Last September, I received an offer from Sam Altman, who wanted to hire me to voice the current ChatGPT 4.0 system," Johansson wrote. "After much consideration and for personal reasons, I declined the offer. Nine months later, my friends, family and the general public all noted how much the newest system named'Sky' sounded like me. When I heard the released demo, I was shocked, angered and in disbelief that Mr. Altman would pursue a voice that sounded so eerily similar to mine that my closest friends and news outlets could not tell the difference."

Fox News Flash top headlines are here. Check out what's clicking on Foxnews.com. Bad weather Tuesday was hampering the search for two men who went over a waterfall while fishing in the Boundary Waters Canoe Area Wilderness of northern Minnesota over the weekend. Nate Skelton told the Star Tribune of Minneapolis that the cloud cover was too low for aerial surveillance and up to 2 inches of rain was anticipated, so the next two days were not promising. Skelton said a search crew was camping on site, waiting for conditions to improve in the remote area, about 100 miles north of Duluth.

Scarlett Johannson has gone to war with OpenAI, and in the battle for public opinion, OpenAI is losing--badly. Last week, OpenAI released an update of its AI chatbot called ChatGPT-4o, which featured a female voice talking to its users. Many people pointed out that the voice, which sometimes seemed to veer into flirtation, was eerily similar to Scarlett Johannson's in the 2013 dystopian sci-fi film Her. OpenAI CEO Sam Altman has long talked about how much the movie inspired the company's products, and even made the connection clear last week by tweeting the title of the movie. But on Monday, Johannson released a statement saying OpenAI had asked her to be the voice of the chatbot, and when she refused, they found a soundalike.

Celebrity break-ups have impacted fans for years, leaving them questioning what the couple's future would have looked like if they stayed together. Now a graphic designer has brought the'what-ifs' to life using AI, revealing the families of famous ex-couples like Brad Pitt and Jennifer Aniston, and Twilight stars Robert Pattinson and Kristen Stewart. Jeremy Pomeroy also recreated the romance of Taylor Swift and Harry Styles, who separated in 2013, generating a little girl and boy who look like the Eras Tour star. The Australian designer used photoshop and advanced AI algorithms to'help generate unique and imaginative images based on existing data and my guidance.' Taylor Swift and Harry Styles (pictured) dated briefly from late 2012 to early 2013 and reportedly broke up due to long-distance.

Ever since Scarlett Johansson voiced an AI assistant in the sci-fi blockbuster'Her', many tech fans have dreamed of making that technology a reality. But it now seems that OpenAI may have pursued that dream too literally as they face accusations of deliberately copying Johansson's voice for ChatGPT's latest update. According to Ms Johansson's statement, the likeness is'so eerily similar to mine that close friends and news outlets could not tell the difference'. Following the allegations, OpenAI's'flirty' voice assistant has now been paused, yet tech fans have been weighing in on whether there really is a resemblance. So, do you think ChatGPT's AI voice sounds like Scarlett Johansson?

'The CyberGuy' Kurt Knutsson joins'Fox & Friends Weekend' to discuss Elon Musk's lawsuit against OpenAI and its CEO over a contractual breach, saying hes right on this one. "Avengers" and "Her" actress Scarlett Johansson revealed that legal action was likely behind OpenAI removing a voice that sounded eerily like hers. A statement released by NPR on Monday explained that OpenAI CEO Sam Altman reached out to Johansson in September about possibly hiring her to voice the ChatGPT 4.0 system. She claimed he suggested her "comforting" voice "could bridge the gap between tech companies and creatives" and help with the "seismic shift concerning humans and Al." Though she rejected the offer after "much consideration and for personal reasons," Johansson was furious to hear the public discuss how the "Sky" voice system resembled hers. Scarlett Johansson said in a statement that she took legal action against OpenAI CEO Sam Altman and the company.

We present BYOKG, a universal question-answering (QA) system that can operate on any knowledge graph (KG), requires no human-annotated training data, and can be ready to use within a day -- attributes that are out-of-scope for current KGQA systems. BYOKG draws inspiration from the remarkable ability of humans to comprehend information present in an unseen KG through exploration -- starting at random nodes, inspecting the labels of adjacent nodes and edges, and combining them with their prior world knowledge. In BYOKG, exploration leverages an LLM-backed symbolic agent that generates a diverse set of query-program exemplars, which are then used to ground a retrieval-augmented reasoning procedure to predict programs for arbitrary questions. BYOKG is effective over both small- and large-scale graphs, showing dramatic gains in QA accuracy over a zero-shot baseline of 27.89 and 58.02 F1 on GrailQA and MetaQA, respectively. On GrailQA, we further show that our unsupervised BYOKG outperforms a supervised in-context learning method, demonstrating the effectiveness of exploration. Lastly, we find that performance of BYOKG reliably improves with continued exploration as well as improvements in the base LLM, notably outperforming a state-of-the-art fine-tuned model by 7.08 F1 on a sub-sampled zero-shot split of GrailQA.

In the current era of digital communication and widespread use of social media, it is crucial to develop an understanding of persuasive techniques employed in written text. This knowledge is essential for effectively discerning accurate information and making informed decisions. To address this need, this paper presents a comprehensive empirical study focused on identifying persuasive techniques in Arabic social media content. To achieve this objective, we utilize Pre-trained Language Models (PLMs) and leverage the ArAlEval dataset, which encompasses two tasks: binary classification to determine the presence or absence of persuasion techniques, and multi-label classification to identify the specific types of techniques employed in the text. Our study explores three different learning approaches by harnessing the power of PLMs: feature extraction, fine-tuning, and prompt engineering techniques. Through extensive experimentation, we find that the fine-tuning approach yields the highest results on the aforementioned dataset, achieving an f1-micro score of 0.865 and an f1-weighted score of 0.861. Furthermore, our analysis sheds light on an interesting finding. While the performance of the GPT model is relatively lower compared to the other approaches, we have observed that by employing few-shot learning techniques, we can enhance its results by up to 20\%. This offers promising directions for future research and exploration in this topic\footnote{Upon Acceptance, the source code will be released on GitHub.}.

We present a new approach for fast and controllable generation of symbolic music based on the simplex diffusion, which is essentially a diffusion process operating on probabilities rather than the signal space. This objective has been applied in domains such as natural language processing but here we apply it to generating 4-bar multi-instrument music loops using an orderless representation. We show that our model can be steered with vocabulary priors, which affords a considerable level control over the music generation process, for instance, infilling in time and pitch and choice of instrumentation -- all without task-specific model adaptation or applying extrinsic control.