paper-with-me

Papers

As bases de dados verbais ADESSE e ViPEr: uma an\'alise constrastiva das constru\cc\~oes locativas em espanhol e em portugu\^es (The verbal databases ADESSE and ViPEr: a contrastive analysis of locative constructs in Spanish and Portuguese)[In Portuguese]

2017-10-01 · WS 2017 10 · Roana Rodrigues, Oto Vale, Laura Alonso Alemany
📄 PDF Abstract BibTeX

Code (0)

등록된 구현이 없습니다.

Similar Papers 제목 키워드 기반

Métodos Empíricos Aplicados à Análise Econômica do Direito

2021-02-20 · Thomas V. Conti

Nas \'ultimas d\'ecadas houve forte mudan\c{c}a no perfil das publica\c{c}\~oes em an\'alise econ\^omica do direito e nos m\'etodos emp\'iricos mais utilizados. Por\'em, nos pr\'oximos anos a mudan\c{c}a pode ser maior e…

ADESSE: Advice Explanations in Complex Repeated Decision-Making Environments

2024-05-31 · Sören Schleibaum, Lu Feng, Sarit Kraus, Jörg P. Müller

In the evolving landscape of human-centered AI, fostering a synergistic relationship between humans and AI agents in decision-making processes stands as a paramount challenge. This work considers a problem setup where an…

Decision MakingDeep Reinforcement Learning

AdaDoS: Adaptive DoS Attack via Deep Adversarial Reinforcement Learning in SDN

2025-10-23 · Wei Shao, Yuhao Wang, Rongguang He, Muhammad Ejaz Ahmed 외 arxiv

Existing defence mechanisms have demonstrated significant effectiveness in mitigating rule-based Denial-of-Service (DoS) attacks, leveraging predefined signatures and static heuristics to identify and block malicious tra…

Reinforcement Learning

MAVIPER: Learning Decision Tree Policies for Interpretable Multi-Agent Reinforcement Learning

2022-05-25 · Stephanie Milani, Zhicheng Zhang, Nicholay Topin, Zheyuan Ryan Shi 외

Many recent breakthroughs in multi-agent reinforcement learning (MARL) require the use of deep neural networks, which are challenging for human experts to interpret and understand. On the other hand, existing work on int…

Multi-agent Reinforcement Learningreinforcement-learningReinforcement LearningReinforcement Learning (RL)

ViPER: Empowering the Self-Evolution of Visual Perception Abilities in Vision-Language Model

2025-10-28 · Juntian Zhang, Song Jin, Chuanqi Cheng, Yuhan Liu 외 arxiv

The limited capacity for fine-grained visual perception presents a critical bottleneck for Vision-Language Models (VLMs) in real-world applications. Addressing this is challenging due to the scarcity of high-quality data…

Reinforcement Learning