Meta-Prompting: Enhancing Language Models with Task-Agnostic Scaffolding

We introduce meta-prompting, an effective scaffolding technique designed to enhance the functionality of language models (LMs). This approach transforms a single LM into a multi-faceted conductor, adept at managing and integrating multiple independent LM queries. By employing high-level instructions, meta-prompting guides the LM to break down complex tasks into smaller, more manageable subtasks. These subtasks are then handled by distinct "expert" instances of the same LM, each operating under specific, tailored instructions. Central to this process is the LM itself, in its role as the conductor, which ensures seamless communication and effective integration of the outputs from these expert models. It additionally employs its inherent critical thinking and robust verification processes to refine and authenticate the end result. This collaborative prompting approach empowers a single LM to simultaneously act as a comprehensive orchestrator and a panel of diverse experts, significantly enhancing its performance across a wide array of tasks. The zero-shot, task-agnostic nature of meta-prompting greatly simplifies user interaction by obviating the need for detailed, task-specific instructions. Furthermore, our research demonstrates the seamless integration of external tools, such as a Python interpreter, into the meta-prompting framework, thereby broadening its applicability and utility. Through rigorous experimentation with GPT-4, we establish the superiority of meta-prompting over conventional scaffolding methods: When averaged across all tasks, including the Game of 24, Checkmate-in-One, and Python Programming Puzzles, meta-prompting, augmented with a Python interpreter functionality, surpasses standard prompting by 17.1%, expert (dynamic) prompting by 17.3%, and multipersona prompting by 15.2%.Comment: https://github.com/suzgunmirac/meta-promptin

The role of structured induction in expert systems

A "structured induction" technique was developed and tested using a rules- from -examples generator together with a chess -specific application package. A drawback of past experience with computer induction, reviewed in this thesis, has been the generation of machine -oriented rules opaque to the user. By use of the structured approach humanly understandable rules were synthesized from expert supplied examples. These rules correctly performed chess endgame classifications of sufficient complexity to be regarded as difficult by international master standard players. Using the "Interactive ID3" induction tools developed by the author, chess experts, with a little programming support, were able to generate rules which solve problems considered difficult or impossible by conventional programming techniques. Structured induction and associated programming tools were evaluated using the chess endgames Icing and Pawn vs. King (Black -tomove) and King and Pawn vs. King and Rook (White -to -move, White Pawn on a7) as trial problems of measurable complexity.Structured solutions to both trial problems are presented, and implications of this work for the design of expert systems languages are assessed

Advances in the Treatment of Renal Cell Carcinoma

This Special Issue of Cancers focuses on new advances in the treatment of renal cell carcinoma, both surgical and pharmacological (and combinations of these), and novel approaches to tackle treatment resistance and improve our understanding of this phenomenon

Leptoquark manoeuvres in the dark: a simultaneous solution of the dark matter problem and the RD(*) anomalies

The measured branching fractions of B-mesons into leptonic final states derived by the LHCb, Belle and BaBar collaborations hint towards the breakdown of lepton flavour universality. In this work we take at face value the so-called RD(*) observables that are defined as the ratios of neutral B-meson charged-current decays into a D-meson, a charged lepton and a neutrino final state in the tau and light lepton channels. A well-studied and simple solution to this charged current anomaly is to introduce a scalar leptoquark S that couples to the second and third generation of fermions. We investigate how S can also serve as a mediator between the Standard Model and a dark sector. We study this scenario in detail and estimate the constraints arising from collider searches for leptoquarks, collider searches for missing energy signals, direct detection experiments and the dark matter relic abundance. We stress that the production of a pair of leptoquarks that decays into different final states (i.e. the commonly called “mixed” channels) provides critical information for identifying the underlying dynamics, and we exemplify this by studying the tτbν and the resonant S plus missing energy channels. We find that direct detection data provides non-negligible constraints on the leptoquark coupling to the dark sector, which in turn affects the relic abundance. We also show that the correct relic abundance can not only arise via standard freeze-out, but also through conversion-driven freeze-out. We illustrate the rich phenomenology of the model with a few selected benchmark points, providing a broad stroke of the interesting connection between lepton flavour universality violation and dark matter.The work of AJ is supported in part by a KIAS Individual Grant No. QP084401 via the Quantum Universe Center at Korea Institute for Advanced Study and by the National Research Foundation of Korea, Grant No. NRF-2019R1A2C1009419. The work of AL was supported by the São Paulo Research Foundation (FAPESP), project 2015/20570-1. JH acknowledges support from the DFG via the Collaborative Research Center TRR 257 and the F.R.S.-FNRS as a Chargé de recherche. The work of AP and GB was funded by the RFBR and CNRS project number 20-52-15005. The work of AP was also supported in part by an AAP-USMB grant and by the Interdisciplinary Scientific and Educational School of Moscow University for Fundamental and Applied Space Research. The work of DS is based upon work supported by the National Science Foundation under Grant No. PHY-1915147. JZ is supported by the Generalitat Valenciana (Spain) through the plan GenT program (CIDEGENT/2019/068), by the Spanish Government (Agencia Estatal de Investigación) and ERDF funds from European Commission (MCIN/AEI/10.13039/501100011033, Grant No. PID2020-114473GB-I00)

Focus topics for the ECFA study on Higgs / Top / EW factories

In order to stimulate new engagement and trigger some concrete studies in areas where further work would be beneficial towards fully understanding the physics potential of an $e^+e^-$ Higgs / Top / Electroweak factory, we propose to define a set of focus topics. The general reasoning and the proposed topics are described in this document.Comment: v3: fixed spelling of two author

SITC cancer immunotherapy resource document: a compass in the land of biomarker discovery.

Since the publication of the Society for Immunotherapy of Cancer\u27s (SITC) original cancer immunotherapy biomarkers resource document, there have been remarkable breakthroughs in cancer immunotherapy, in particular the development and approval of immune checkpoint inhibitors, engineered cellular therapies, and tumor vaccines to unleash antitumor immune activity. The most notable feature of these breakthroughs is the achievement of durable clinical responses in some patients, enabling long-term survival. These durable responses have been noted in tumor types that were not previously considered immunotherapy-sensitive, suggesting that all patients with cancer may have the potential to benefit from immunotherapy. However, a persistent challenge in the field is the fact that only a minority of patients respond to immunotherapy, especially those therapies that rely on endogenous immune activation such as checkpoint inhibitors and vaccination due to the complex and heterogeneous immune escape mechanisms which can develop in each patient. Therefore, the development of robust biomarkers for each immunotherapy strategy, enabling rational patient selection and the design of precise combination therapies, is key for the continued success and improvement of immunotherapy. In this document, we summarize and update established biomarkers, guidelines, and regulatory considerations for clinical immune biomarker development, discuss well-known and novel technologies for biomarker discovery and validation, and provide tools and resources that can be used by the biomarker research community to facilitate the continued development of immuno-oncology and aid in the goal of durable responses in all patients

A Survey of Monte Carlo Tree Search Methods

Monte Carlo tree search (MCTS) is a recently proposed search method that combines the precision of tree search with the generality of random sampling. It has received considerable interest due to its spectacular success in the difficult problem of computer Go, but has also proved beneficial in a range of other domains. This paper is a survey of the literature to date, intended to provide a snapshot of the state of the art after the first five years of MCTS research. We outline the core algorithm's derivation, impart some structure on the many variations and enhancements that have been proposed, and summarize the results from the key game and nongame domains to which MCTS methods have been applied. A number of open research questions indicate that the field is ripe for future work