Tootfinder

DHL / Deutsche Post
Die Post mal wieder.
Seitdem ich in HH wohne kommen nur ~2/3 der Briefe an. Der Rest wird retourniert; inklusive Bankomatkarten und was-weiß-ich-nicht-alles. The unknown unknowns.
Jetzt dachte ich mir, hm, okay, bestell ich 'ne Briefankündigung — dann hab ich hinterher was für die Bundesnetzagentur zum Stunk machen. Die Post ignoriert das Problem auf Anfrage und Anschreiben immerhin geflissentlich.
Uuund was kommt seit zwei Wochen nicht an? Der Briefankündigungsfreischaltbrief.
..ich weiß auch nicht, was ich erwartet habe :D

ClimRetrieve: A Benchmarking Dataset for Information Retrieval from Corporate Climate Disclosures
Tobias Schimanski, Jingwei Ni, Roberto Spacey, Nicola Ranger, Markus Leippold
https://arxiv.org/abs/2406.09818

ClimRetrieve: A Benchmarking Dataset for Information Retrieval from Corporate Climate Disclosures
To handle the vast amounts of qualitative data produced in corporate climate communication, stakeholders increasingly rely on Retrieval Augmented Generation (RAG) systems. However, a significant gap remains in evaluating domain-specific information retrieval - the basis for answer generation. To address this challenge, this work simulates the typical tasks of a sustainability analyst by examining 30 sustainability reports with 16 detailed climate-related questions. As a result, we obtain a data…

Tree Search for Simultaneous Move Games via Equilibrium Approximation
Ryan Yu, Alex Olshevsky, Peter Chin
https://arxiv.org/abs/2406.10411 https://arxiv.org/pdf/2406.10411
arXiv:2406.10411v1 Announce Type: new
Abstract: Neural network supported tree-search has shown strong results in a variety of perfect information multi-agent tasks. However, the performance of these methods on partial information games has generally been below competing approaches. Here we study the class of simultaneous-move games, which are a subclass of partial information games which are most similar to perfect information games: both agents know the game state with the exception of the opponent's move, which is revealed only after each agent makes its own move. Simultaneous move games include popular benchmarks such as Google Research Football and Starcraft.
In this study we answer the question: can we take tree search algorithms trained through self-play from perfect information settings and adapt them to simultaneous move games without significant loss of performance? We answer this question by deriving a practical method that attempts to approximate a coarse correlated equilibrium as a subroutine within a tree search. Our algorithm works on cooperative, competitive, and mixed tasks. Our results are better than the current best MARL algorithms on a wide range of accepted baseline environments.