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pro vyhledávání: '"Boi, P."'
Copyright-Aware Incentive Scheme for Generative Art Models Using Hierarchical Reinforcement Learning
Generative art using Diffusion models has achieved remarkable performance in image generation and text-to-image tasks. However, the increasing demand for training data in generative art raises significant concerns about copyright infringement, as mod
Externí odkaz:
http://arxiv.org/abs/2410.20180
The increasing sophistication of text-to-image generative models has led to complex challenges in defining and enforcing copyright infringement criteria and protection. Existing methods, such as watermarking and dataset deduplication, fail to provide
Externí odkaz:
http://arxiv.org/abs/2408.16634
To address this gap, our study introduces the concept of causal epistemic consistency, which focuses on the self-consistency of Large Language Models (LLMs) in differentiating intermediates with nuanced differences in causal reasoning. We propose a s
Externí odkaz:
http://arxiv.org/abs/2409.00103
Autor:
Borges, Beatriz, Foroutan, Negar, Bayazit, Deniz, Sotnikova, Anna, Montariol, Syrielle, Nazaretzky, Tanya, Banaei, Mohammadreza, Sakhaeirad, Alireza, Servant, Philippe, Neshaei, Seyed Parsa, Frej, Jibril, Romanou, Angelika, Weiss, Gail, Mamooler, Sepideh, Chen, Zeming, Fan, Simin, Gao, Silin, Ismayilzada, Mete, Paul, Debjit, Schöpfer, Alexandre, Janchevski, Andrej, Tiede, Anja, Linden, Clarence, Troiani, Emanuele, Salvi, Francesco, Behrens, Freya, Orsi, Giacomo, Piccioli, Giovanni, Sevel, Hadrien, Coulon, Louis, Pineros-Rodriguez, Manuela, Bonnassies, Marin, Hellich, Pierre, van Gerwen, Puck, Gambhir, Sankalp, Pirelli, Solal, Blanchard, Thomas, Callens, Timothée, Aoun, Toni Abi, Alonso, Yannick Calvino, Cho, Yuri, Chiappa, Alberto, Sclocchi, Antonio, Bruno, Étienne, Hofhammer, Florian, Pescia, Gabriel, Rizk, Geovani, Dadi, Leello, Stoffl, Lucas, Ribeiro, Manoel Horta, Bovel, Matthieu, Pan, Yueyang, Radenovic, Aleksandra, Alahi, Alexandre, Mathis, Alexander, Bitbol, Anne-Florence, Faltings, Boi, Hébert, Cécile, Tuia, Devis, Maréchal, François, Candea, George, Carleo, Giuseppe, Chappelier, Jean-Cédric, Flammarion, Nicolas, Fürbringer, Jean-Marie, Pellet, Jean-Philippe, Aberer, Karl, Zdeborová, Lenka, Salathé, Marcel, Jaggi, Martin, Rajman, Martin, Payer, Mathias, Wyart, Matthieu, Gastpar, Michael, Ceriotti, Michele, Svensson, Ola, Lévêque, Olivier, Ienne, Paolo, Guerraoui, Rachid, West, Robert, Kashyap, Sanidhya, Piazza, Valerio, Simanis, Viesturs, Kuncak, Viktor, Cevher, Volkan, Schwaller, Philippe, Friedli, Sacha, Jermann, Patrick, Kaser, Tanja, Bosselut, Antoine
AI assistants are being increasingly used by students enrolled in higher education institutions. While these tools provide opportunities for improved teaching and education, they also pose significant challenges for assessment and learning outcomes.
Externí odkaz:
http://arxiv.org/abs/2408.11841
Despite the remarkable performance of Large Language Models (LLMs) in natural language processing tasks, they still struggle with generating logically sound arguments, resulting in potential risks such as spreading misinformation. To address this iss
Externí odkaz:
http://arxiv.org/abs/2408.03618
Autor:
Abbrescia, M., Avanzini, C., Baldini, L., Ferroli, R. Baldini, Batignani, G., Battaglieri, M., Boi, S., Bossini, E., Carnesecchi, F., Cavazza, F., Cicalò, C., Cifarelli, L., Coccetti, F., Coccia, E., Corvaglia, A., De Gruttola, D., De Pasquale, S., Galante, L., Garbini, M., Gnesi, I., Gramegna, F., Grazzi, S., Hatzifotiadou, D., La Rocca, P., Liu, Z., Mandaglio, G., Margotti, A., Maron, G., Mazziotta, M. N., Mulliri, A., Nania, R., Noferini, F., Nozzoli, F., Palmonari, F., Panareo, M., Panetta, M. P., Paoletti, R., Pellegrino, C., Perasso, L., Pinazza, O., Pinto, C., Pisano, S., Riggi, F., Righini, G., Ripoli, C., Rizzi, M., Sartorelli, G., Scapparone, E., Schioppa, M., Scioli, G., Scribano, A., Selvi, M., Taiuti, M., Terreni, G., Trifirò, A., Trimarchi, M., Vistoli, C., Votano, L., Williams, M. C. S., Zichichi, A., Zuyeuski, R.
The Extreme Energy Events (EEE) Project, a joint project of the Centro Fermi (Museo Storico della Fisica e Centro Studi e Ricerche "E.Fermi") and INFN, has a dual purpose: a scientific research program on cosmic rays at ground level and an intense ou
Externí odkaz:
http://arxiv.org/abs/2408.01802
Disentangling the stellar population in the central galaxy from the intrahalo light can help us shed light on the formation history of the host halo, as the properties of the stellar components are expected to retain traces of its formation history.
Externí odkaz:
http://arxiv.org/abs/2407.00838
Understanding commonsense causality is a unique mark of intelligence for humans. It helps people understand the principles of the real world better and benefits the decision-making process related to causation. For instance, commonsense causality is
Externí odkaz:
http://arxiv.org/abs/2406.19307
Large language models (LLMs) have been shown to perform better when asked to reason step-by-step before answering a question. However, it is unclear to what degree the model's final answer is faithful to the stated reasoning steps. In this paper, we
Externí odkaz:
http://arxiv.org/abs/2402.13950
Autor:
Cui, Shaobo, Milikic, Lazar, Feng, Yiyang, Ismayilzada, Mete, Paul, Debjit, Bosselut, Antoine, Faltings, Boi
Defeasibility in causal reasoning implies that the causal relationship between cause and effect can be strengthened or weakened. Namely, the causal strength between cause and effect should increase or decrease with the incorporation of strengthening
Externí odkaz:
http://arxiv.org/abs/2401.03183