Expanding Search Spaces
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Step-by-Step Optimization-like Reasoning in LLMs over Expanding Search Spaces
arXiv:2606.05464v1 Announce Type: new Abstract: Verifiable reward training has improved mathematical and coding reasoning, but these domains capture only part of step-by-step decision making. Many real-world tasks require finding a high-value feasible plan among many valid alternatives. We introduce OPT*, a scalable family of optimization-style tasks for training and evaluating LLM step-by-step optimization-like reasoning along a complexity axis: each task provides a feasibility checker and...
Quality-Diversity Search in Sound Generation: Investigating Innovation Engines for Audio Exploration
arXiv:2606.09780v1 Announce Type: new Abstract: This study addresses the challenges composers and sound designers face in creating and refining tools to achieve their musical goals. Using evolutionary processes to promote diversity and foster serendipitous discoveries, we automate the search through uncharted sonic spaces for sound discovery, arguing that diversity-promoting algorithms can bridge the gap between the theoretical realisation and practical accessibility of sounds.
Smart Transportation Without Neurons -- Fair Metro Network Expansion with Tabular Reinforcement Learning
arXiv:2606.04167v1 Announce Type: new Abstract: We tackle the Metro Network Expansion Problem (MNEP), a subset of the Transport Network Design Problem (TNDP), which focuses on expanding metro systems to satisfy travel demand. Traditional methods rely on exact and heuristic approaches that require expert-defined constraints to reduce the search space. Recently, deep reinforcement learning (Deep RL) has emerged due to its effectiveness in complex sequential decision-making processes-it...
From Flat to Hierarchical: Evolving Tree-structured Thoughts for Fine-grained Alpha Mining
arXiv:2508.16334v2 Announce Type: replace Abstract: Alpha mining, aimed at discovering predictive return signals, is typically formulated as symbolic regression. Traditional symbolic methods suffer from search inefficiency and biased prior knowledge. Recently, Large Language Models (LLMs) have emerged as a promising alternative, automatically generating textual thoughts and executable codes to achieve both efficient and interpretable alpha mining.
Exposing Hidden Biases in Text-to-Image Models via Automated Prompt Search
arXiv:2512.08724v3 Announce Type: replace Abstract: Text-to-image (TTI) diffusion models have achieved remarkable visual quality, yet they have been repeatedly shown to exhibit social biases across sensitive attributes such as gender, race and age. To mitigate these biases, existing approaches frequently depend on curated prompt datasets - either manually constructed or generated with large language models (LLMs) - as part of their training and/or evaluation procedures. Beside the curation...
One southern city you've never heard of is growing faster than anywhere else in America
CELINA, Texas — A few years ago, the city of Celina was a quiet ranching town surrounded by open fields an hour north of Dallas. Now, it’s the fastest-growing city in America, where bulldozers outnumber cattle and sprawling new neighborhoods are rising almost overnight. The boom transforming this once-rural community reflects the explosive growth reshaping North Texas, as families and businesses push beyond city hubs in search of more affordable housing, better schools and more space.
One southern city you've never heard of is growing faster than anywhere else in America
CELINA, Texas — A few years ago, the city of Celina was a quiet ranching town surrounded by open fields an hour north of Dallas. Now, it’s the fastest-growing city in America, where bulldozers outnumber cattle and sprawling new neighborhoods are rising almost overnight. The boom transforming this once-rural community reflects the explosive growth reshaping North Texas, as families and businesses push beyond city hubs in search of more affordable housing, better schools and more space.
Hidden supermassive black hole pairs may finally have a visible signal
Hidden supermassive black hole pairs may finally have a visible signal - Date: - June 5, 2026 - Source: - University of Oxford - Summary: - Scientists have proposed a new method for finding tightly bound supermassive black hole pairs by searching for stars that flash repeatedly as their light is magnified by the black holes’ gravity. The timing and brightness of these bursts could provide a unique fingerprint of black holes slowly spiraling toward a future collision. Astronomers from the...
The Evolution of 'More Like This'
In many search scenarios, the user does not start from an empty query box, but from an existing result. A user opens an article and wants to find related material. A buyer views a product card and looks for close alternatives.
Grep this: Microsoft grafts (most) Linux commands onto Windows
Steve Ballmer’s darkest fear has come to pass: Linux has worked itself into the deepest innards of Microsoft Windows itself. At the company’s annual Build developer conference this week, Microsoft released coreutils, a Rust-built multi-call binary file for Windows that serves over 75 Unix commands directly in the Windows CMD and PowerShell command lines – including favorites such as cat, ls, grep, and head. They join Linux favorites curl and sudo which were earlier added to the Microsoft...