Tootfinder

Northvolt-Pleite: Rechnungshof soll Förderung unter die Lupe nehmen
Hat die Landesregierung den Landtag umfassend genug über die Northvolt-Förderung informiert? Diese Frage ist nun ein Fall für den Landesrechnungshof.

Reasoning about Uncertainty: Do Reasoning Models Know When They Don't Know?
Zhiting Mei, Christina Zhang, Tenny Yin, Justin Lidard, Ola Shorinwa, Anirudha Majumdar
https://arxiv.org/abs/2506.18183

Reasoning about Uncertainty: Do Reasoning Models Know When They Don't Know?
Reasoning language models have set state-of-the-art (SOTA) records on many challenging benchmarks, enabled by multi-step reasoning induced using reinforcement learning. However, like previous language models, reasoning models are prone to generating confident, plausible responses that are incorrect (hallucinations). Knowing when and how much to trust these models is critical to the safe deployment of reasoning models in real-world applications. To this end, we explore uncertainty quantification…

R4ec: A Reasoning, Reflection, and Refinement Framework for Recommendation Systems
Hao Gu, Rui Zhong, Yu Xia, Wei Yang, Chi Lu, Peng Jiang, Kun Gai
https://arxiv.org/abs/2507.17249

R4ec: A Reasoning, Reflection, and Refinement Framework for Recommendation Systems
Harnessing Large Language Models (LLMs) for recommendation systems has emerged as a prominent avenue, drawing substantial research interest. However, existing approaches primarily involve basic prompt techniques for knowledge acquisition, which resemble System-1 thinking. This makes these methods highly sensitive to errors in the reasoning path, where even a small mistake can lead to an incorrect inference. To this end, in this paper, we propose $R^{4}$ec, a reasoning, reflection and refinement…

Reinforcement Learning in hyperbolic space for multi-step reasoning
Tao Xu, Dung-Yang Lee, Momiao Xiong
https://arxiv.org/abs/2507.16864 https://

Reinforcement Learning in hyperbolic space for multi-step reasoning
Multi-step reasoning is a fundamental challenge in artificial intelligence, with applications ranging from mathematical problem-solving to decision-making in dynamic environments. Reinforcement Learning (RL) has shown promise in enabling agents to perform multi-step reasoning by optimizing long-term rewards. However, conventional RL methods struggle with complex reasoning tasks due to issues such as credit assignment, high-dimensional state representations, and stability concerns. Recent advanc…

ThinkAct: Vision-Language-Action Reasoning via Reinforced Visual Latent Planning
Chi-Pin Huang, Yueh-Hua Wu, Min-Hung Chen, Yu-Chiang Frank Wang, Fu-En Yang
https://arxiv.org/abs/2507.16815

ThinkAct: Vision-Language-Action Reasoning via Reinforced Visual Latent Planning
Vision-language-action (VLA) reasoning tasks require agents to interpret multimodal instructions, perform long-horizon planning, and act adaptively in dynamic environments. Existing approaches typically train VLA models in an end-to-end fashion, directly mapping inputs to actions without explicit reasoning, which hinders their ability to plan over multiple steps or adapt to complex task variations. In this paper, we propose ThinkAct, a dual-system framework that bridges high-level reasoning wit…

Former Trump Judge Recommended For Disbarment - Above the Law
https://abovethelaw.com/2025/08/former-trump-judge-recommended-for-disbarment/

ConciseHint: Boosting Efficient Reasoning via Continuous Concise Hints during Generation
Siao Tang, Xinyin Ma, Gongfan Fang, Xinchao Wang
https://arxiv.org/abs/2506.18810

ConciseHint: Boosting Efficient Reasoning via Continuous Concise Hints during Generation
Recent advancements in large reasoning models (LRMs) like DeepSeek-R1 and OpenAI o1 series have achieved notable performance enhancements on complex reasoning tasks by scaling up the generation length by Chain-of-Thought (CoT). However, an emerging issue is their inclination to produce excessively verbose reasoning processes, leading to the inefficiency problem. Existing literature on improving efficiency mainly adheres to the before-reasoning paradigms such as prompting and reasoning or fine-t…

Gesetzentwurf: Bankkunden sollen mehr Rechte beim Dispo bekommen
Online-Shopping auf Rechnung soll eingeschränkt werden, da vor allem junge Menschen dadurch leicht den Überblick verlieren und in die Schuldenfalle geraten.

Insolvenzverwalter: Potenzielle Investoren für Meyer Burger
Wie gut sind die Rettungschancen für den Solarmodulhersteller Meyer Burger? Der Insolvenzverwalter spricht von einer guten Resonanz bei der Investorensuche.

Galaxy Z Fold 7 und mehr: Samsung kündigt Unpacked-Event für 9. Juli an
Samsung will Anfang Juli im Zuge eines Unpacked-Events neue Produkte vorstellen. Neben Foldables können Konsumenten auch mit Galaxy-Watches rechnen.