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VideoConviction: A Multimodal Benchmark for Human Conviction and Stock Market Recommendations
Michael Galarnyk, Veer Kejriwal, Agam Shah, Yash Bhardwaj, Nicholas Meyer, Anand Krishnan, Sudheer Chava
https://arxiv.org/abs/2507.08104

VideoConviction: A Multimodal Benchmark for Human Conviction and Stock Market Recommendations
Social media has amplified the reach of financial influencers known as "finfluencers," who share stock recommendations on platforms like YouTube. Understanding their influence requires analyzing multimodal signals like tone, delivery style, and facial expressions, which extend beyond text-based financial analysis. We introduce VideoConviction, a multimodal dataset with 6,000+ expert annotations, produced through 457 hours of human effort, to benchmark multimodal large language models (MLLMs) an…

Crosslisted article(s) found for cs.NI. https://arxiv.org/list/cs.NI/new
[1/1]:
- Robust Heuristic Algorithm Design with LLMs
Pantea Karimi, Dany Rouhana, Pooria Namyar, Siva Kesava Reddy Kakarla, Venkat Arun, Behnaz Arzani

Das kaiserliche U-Boot ist zerbrochen. Deutschland am Boden.

Doubly Separable Spacetimes and Symmetry Constraints on their Self-Gravitating Matter Content
Prashant Kocherlakota, Ramesh Narayan
https://arxiv.org/abs/2507.18706 https://

Doubly Separable Spacetimes and Symmetry Constraints on their Self-Gravitating Matter Content
A popular approach to constructing exact stationary and axisymmetric nonvacuum solutions in general relativity has been to use solution-generating techniques. Here we revisit a recent variant of the Newman-Janis-Azreg-Ainou algorithm, restricted to asymptotically-flat spacetimes, and demonstrate that this method exclusively generates Konoplya-Stuchlik-Zhidenko spacetimes. Therefore, the equations for geodesic motion and scalar-wave propagation are both separable. We call these "doubly separable…

Prospects for EMRI/MBH parameter estimation using Quasi-Periodic Eruption timings: short-timescale analysis
Joheen Chakraborty, Lisa V. Drummond, Matteo Bonetti, Alessia Franchini, Shubham Kejriwal, Giovanni Miniutti, Riccardo Arcodia, Scott A. Hughes, Francisco Duque, Erin Kara, Alberto Sesana, Margherita Giustini, Amedeo Motta, Kevin Burdge
https://

Prospects for EMRI/MBH parameter estimation using Quasi-Periodic Eruption timings: short-timescale analysis
Quasi-Periodic Eruptions (QPEs) are luminous, recurring X-ray outbursts from galactic nuclei, with timescales of hours to days. While their origin remains uncertain, leading models invoke accretion disk instabilities or the interaction of a massive black hole (MBH) with a lower-mass secondary in an extreme mass ratio inspiral (EMRI). EMRI scenarios offer a robust framework for interpreting QPEs by characterizing observational signatures associated with the secondary's orbital dynamics. This, in…

Extremal Testing for Network Software using LLMs
Rathin Singha, Harry Qian, Srinath Saikrishnan, Tracy Zhao, Ryan Beckett, Siva Kesava Reddy Kakarla, George Varghese
https://arxiv.org/abs/2507.11898

Extremal Testing for Network Software using LLMs
Physicists often manually consider extreme cases when testing a theory. In this paper, we show how to automate extremal testing of network software using LLMs in two steps: first, ask the LLM to generate input constraints (e.g., DNS name length limits); then ask the LLM to generate tests that violate the constraints. We demonstrate how easy this process is by generating extremal tests for HTTP, BGP and DNS implementations, each of which uncovered new bugs. We show how this methodology extends t…

Replaced article(s) found for cs.NI. https://arxiv.org/list/cs.NI/new
[1/1]:
- Eywa: Automating Model Based Testing using LLMs
Mondal, Singha, Millstein, Varghese, Beckett, Kakarla