dataesr/scientific-paragraphs-categorization huggingface dataset:
Detecting and explaining unfairness in consumer contracts through memory networks (Ruggeri et al. 2022). Commentary by Serena Villata This paper presents an important contribution to the field of AI and Law by proposing a novel Natural Language Processing (NLP) approach to the identification of unfair clauses in a class of consumer contracts. More precisely, terms of service (ToS) are consumer contracts governing the relation between providers and users. In this context, clauses in ToS which cause a significant imbalance in the parties' rights and obligations are deemed unfair according to Consumer Law. Despite actions taken by the enforcers to control the quality of ToS, online providers still tend to employ unfair clauses in these documents. This became a major issue with the General Data Protection Regulation (GDPR) regulation 34.
However, they can only rely on a automated system if this system can "explain" the rationale behind the advice, i. e. indicate not only that a certain clause of a ToS is unfair, but why it is unfair. This is the main motivation for the contribution presented in this paper. This paper is based on a project devoted to the AI and Law field, the CLAU-DETTE project 35 which aimed at the empowerment of the consumer via AI, by investigating ways to automate reading and legal assessment of online consumer contracts and privacy policies with NLP techniques. The final goal was to evaluate the compliance of these contracts and privacy policies with EU consumer and data protection law. The results presented in this paper are the latest achievements obtained in the framework of this project. Two main contributions are presented in this paper: first, the creation of an annotated dataset for the identification and classification of unfair clauses in ToS documents, and second, the architecture designed to automatically address this task.
Concerning the creation of an annotated dataset, this is an important contribution of the paper as the lack of existing annotated linguistic legal resources is a key issue in the AI and Law field as it slows the development of automatic approaches to ease and support jurists' activity. The dataset is composed of 100 ToS documents. These documents are standard terms available on provider's websites for review by potential and current consumers. The ToS collected in the dataset were downloaded and analyzed over a period of eighteen months by four legal experts. Potentially unfair clauses were tagged using the guidelines carefully defined by the authors. In particular, the annotation task aimed at identifying in the ToS the following clauses: 34 See https:// gdpr-info. eu/ 35  Contissa et al.
Together, these three techniques improve the convergence of NLOS transient path tracing with little cost. • We implement our techniques inside a custom transientaware version of Mitsuba 2  [14]. It provides many useful features such as CPU and GPU parallelism, simulation of the polarization of the light, and could be used for differentiable transient rendering. We compare our results with a reference implementation  [13] , with lower computational complexity, faster convergence and lower rendering times. • Finally, we demonstrate the usefulness of our data by using it to reconstruct NLOS scenes using the phasor fields framework proposed by Liu et al. [10].
On top of such formulation, several steady-state rendering algorithms have been adapted, such as bidirectional path tracing  [13]  or progressive photon beams  [36] , as well as simplified models  [37, 38]  or extensions to include polarization  [39] , or also include fluorescence  [40]. The implementation of our technique is an extension of the Mitsuba2 library  [14]  so it can also account for polarization. These ideas have also been applied to the NLOS domain: Hullin  [41]  and Heide et al. [42]  simulate transient light transport to speed up the expensive data capture. Our proposed technique is also tailored towards NLOS setups, but mainly focused on noise reduction for pure transient rendering. Other authors avoid accounting for paths with more than three bounces, simplifying the path integral to obtain efficient results for learning-based reconstruction  [28, 29].
Non-line-of-sight path tracing In this section, we introduce our contributions by adapting the transient path tracing algorithm to simulate NLOS data capture. The setup described in Fig. 1  uses a single laser beam to generate a time-resolved image I(x s , y s , t), where (x s , y s ) parametrize the 2D space of the visible surfaces of the camera (the relay wall). We define this 2D-to-3D map as M s (x s , y s ) → x s , with x s being a 3D point visible from the camera. A common setup repeats this measurement for multiple laser positions on the visible surfaces, which results in a fivedimensional signal I(x l , y l , x s , y s , t), with (x l , y l ) parametrizing the 2D space of laser positions. For simplicity, we will refer to the three-dimensional case I(x s , y s , t), since extending to five dimensions just requires repeating the same experiment, changing the orientation of the laser.
Lastly, Fig. 10  shows two complex scenes in closed rooms, based on the Z-NLOS dataset  [46]. They are challenging scenes for NLOS reconstruction algorithms, mainly because of the multipath interference caused by indirect bounces. Note how the multiple wavefronts that appear in the relay wall are caused by the hidden geometry, and how their time is related to the distance of each geometry point to the emission source in the center of the relay wall. Polarization. As our implementation is done in Mitsuba 2, it allows for the simulation of polarization of the light. Fig. 13  shows a Cornell Box scene with three spheres: two have a dielectric material and one has a conductor material. It shows the polarization state of the light using the four Stokes vector components, for both the steady and transient states.
The proposed laser sampling technique, that creates a virtual point light (VPL) in the relay wall, greatly reduces variance in the simulation. As with all VPL-based methods, this is a form of bidirectional path tracing  [47]  with single-segment light subpaths. Of course, larger light subpaths could be used for larger variance reduction via MIS, but that would make the wavefront-based GPU implementation in Mitsuba 2 significantly more complex while introducing some overhead due to a quadratic growth on shadow connections during MIS. Going beyond, the guiding technique we propose for sampling the contribution of hidden objects could introduce additional complexity in the computation of the path contributions, resulting in a form of tridirectional path tracing  [48]. Lastly, we have implemented our technique on top of the Mitsuba 2 rendering software, so in practice we take advantage of its parallelization and vectorization capabilities and its ability to include more sophisticated light transport information such as polarization, extending it to transient state.
Acknowledgments This work has received funding from the  European Research Council (ERC)  under the European Union's  Horizon 2020 research and innovation programme  (project  CHAMELEON , Grant No  682080 ), the  EU   MSCA-ITN programme  (project  PRIME , Grant No  956585 ) and  MCIN/AEI/10. 13039/501100011033  (project  VIR-TUALIGHT , Grant  PID2019-105004GB-I00 ). Additionally,  Diego Royo  was supported by a  Gobierno de Aragón  ( 2021-2025 ) predoctoral grant.
Diego Royo: Conceptualization, Software, Validation, Visualization, Writing -original draft. Jorge García: Software, Validation, Visualization. Adolfo Muñoz: Conceptualization, Validation, 1 https://github. com/diegoroyo/mitsuba2-transient-nlos Writing -review & editing, Supervision. Adrian Jarabo: Conceptualization, Validation, Writing -review & editing, Supervision.
Critical facilities Parallel to developments for "normal risk" construction, numerous seismic hazard safety studies for critical facilities were performed on a site-specific basis, starting with development of nuclear energy (i. e. , Règle Fondamentale de  Sûreté [RFS1. 2c] in 1981 and updated in 2001 [RFS 2001-01] ), followed by chemical industries [Arrêté du 10 mai 1993, updated in Arrêté du 15 février 2018] and dams [Arrêté du 6 août 2018]. The history of seismic zonation in France since the 1970s would have been very different without the developments performed for the nuclear industry that made some key contributions essential for several components of SHA: • Creation and maintenance of the SisFrance database [www. sisfrance. net, maintained jointly by BRGM, EDF, and IRSN; see, e. g. ,  Lambert et al.
[1996] ,  Lambert [2009] ,  Scotti et al. [2004] , or  Jomard et al. [2021]  in the present issue] helped achieve a major breakthrough in the knowledge of historical seismicity. The SisFrance database has been used to derive several earthquake catalogs for SHA, including the French Seismic CATalog (FCAT) published by  Manchuel et al. [2018]. • Knowledge of the seismotectonics at large in mainland France. The seismotectonic map project for France  [Goguel et al. , 1985]  further triggered and provided background research on seismotectonics [e. g. ,  Grellet et al. , 1993] , neotectonics, and fault characterization. The first fault database for France was published by  Jomard et al. [2017]. Although the deterministic approach (RFS2001-01) has been, and still is, the official approach imposed by the control authorities in France, the nuclear community first attempted to develop a probabilistic approach for the French territory in the early 1980s  [Hendrickx, 1981 , Dadou, 1981 , Dadou et al.
Earthquake catalog used All earthquake catalogs rely on the SisFrance macroseismic database for the historical period; however, there are major differences in how magnitudes and locations are determined for historical events. In early publications [e. g. ,  Bottard and Ferrieux, 1992 , Dominique and André, 2000 , Marin et al. , 2004 , Secanell et al. , 2008] , historical magnitudes were evaluated based on a single intensity assignment, epicentral intensity, and an empirical relation. As emphasized in  Bakun et al. [2011] , epicentral intensity alone cannot provide accurate estimates of location and magnitude, nor estimates of their uncertainty; therefore, most PSHA studies after 2004 include a historical catalog with magnitudes inverted from the set of intensity observations available for each earthquake, applying intensity-magnitude relationships.
, 2008 , Bozorgnia et al. , 2014;  or European models based on the RESORCE database,  Douglas et al. , 2014]. Use of the LDG catalog thus implies a magnitude conversion known to be responsible for strong uncertainties. Some authors [e. g. ,  Clément et al. , 2004, Beauval and Scotti, 2004]  prefer to make a conservative assumption that M L is equivalent to M S , whereas other authors [e. g. ,  Marin et al. , 2004]  apply an inhouse M L -M S conversion equation. After 2017, hazard studies use the SiHex instrumental catalog in M W that was built by a consortium of French seismologic networks and observatories  [Cara et al. , 2015]. This catalog constitutes the instrumental part of the FCAT catalog  [Manchuel et al. , 2018]. Moment magnitudes in this catalog have been obtained by applying different magnitude conversion equations  [Cara et al.
, 2015]. This catalog is ready for use in hazard assessment studies. Several authors note issues related to estimation of M W in SiHex [e. g. ,  Laurendeau et al. , 2019]  and the apparent lack of homogeneity of instrumental M W magnitudes with M W estimates for historical events in FCAT  [Beauval et al. , 2020; Figure   1 ]. Additional work is still needed. The academic community has produced the Si-Hex catalog; however, unlike our neighboring countries there has never been an earthquake catalog for France that represents an authoritative dataset for seismic hazard studies which merges historical and   [Manchuel et al. , 2018] , issues related to inhomogeneity between the historical and instrumental periods. Left: cumulative number of events versus time: 3. 5 ≤ M W < 3. 8, 3. 8 ≤ M W < 4.
This impact is related to the minimum magnitude used in recurrence modeling [M W 3. 2 in  Beauval et al. , 2020]. In areas where earthquake recurrence models are poorly constrained because of scarcity of data, it is worth going down to lower magnitudes. The number of clustered events increases with decreasing magnitude [see, e. g. ,  Drouet et al. , 2020]. Issues related to the presence of non-tectonic events in an earthquake catalog increase with decreasing magnitude [e. g. , quarry blasts;  Cara et al. , 2015]. Given the scarcity of data in some regions, a lower magnitude range needs to be included in modeling; however, in this case, decisions related to declustering might have a larger impact on hazard, but testing is needed. It is common to decluster an earthquake catalog before modeling recurrence in hazard studies.
Solid line: model. Symbols: observed rates estimated from the catalog. same limits: (1) determination of the time window of completeness is extremely uncertain for upper magnitude range intervals with too few events; (2) for lower magnitude intervals, seismic rates can fluctuate for reasons that are not natural, due to modifications in the determination of the magnitude along the years or due to the application of magnitude conversion equations. One way to circumvent these issues is to apply methods that are not dependent on earthquake data. For the historical part of the catalog, completeness can be estimated by, "looking outside the datasets; that is, investigating the way historical records have been produced, preserved and retrieved",  Stucchi et al. [2004]. For time periods in which no earthquakes were reported, historians propose assessing whether historical sources reported other events (either natural or political) or no events at all [see  Stucchi et al.
Fault models To account for faults in a seismic hazard study, a minimum level of information regarding its 3D geometry and amount of deformation accumulating on the fault is required. This level of detail is not available for most faults in France, and only four publications explicitly consider a fault model (see Supplementary Table  2 ). Three of these [i. e. ,  Marin et al. , 2004 , Clément et al. , 2004 , Martin et al. , 2017]  focus on the Provence area, including faults such as the Middle Durance and Trévaresse faults. The fourth publication [i. e. ,  Chartier et al. , 2017a]  studies the Upper Rhine Graben; fault parameters are from the fault database published by  Jomard et al. [2017]. In the early publications by  Marin et al. [2004]  and  Clément et al. [2004] , earthquake rates on the faults are inferred from the GR frequency-magnitude distribution established at the level of the source zone (hosting the faults).
As a result of this effort, the first fault database, which was published by  Jomard et al. [2017]  and does not cover all of France, will be completed in the short term. Their findings are key for establishing future seismogenic source models for the country and contributing to the development of more realistic fault models in the best-characterized regions. Depending on the level of details obtained, segmentation might be relaxed for some faults in the future, and fault connectivity may be accounted for [e. g. ,  Chartier et al. , 2017b , Valentini et al. , 2020].
Ground-motion models used All selected studies deliver hazard in terms of ground motions, with the exception of the early PSHA study by  Bottard and Ferrieux [1992] , which applies equations that predict the attenuation of macroseismic intensities with distance and deliver a hazard map in intensity. France is a low-to-moderate seismicity region, and, even at present, despite the RAP-RESIF instrumentation program that was launched in the mid-1990s, there are still very few recordings available for the magnitude and distance ranges that control seismic hazard at return periods of interest. A ground-motion model must be established on an extended dataset to be valid and cover broad magnitude and distance ranges to obtain a reliable estimate of median ground-motion levels and associated variability.
Ground-motion databases are thus constituted of gathering recordings from large spatial areas. PSHA studies by Dominique and André  [2000] ,  Clément et al. [2004] , and  Secanell et al. [2008]  use the pan-European and Middle East models of  Ambraseys [1995]  and  Ambraseys et al. [1996]. At that time, European models did not include French recordings. Similarly, the Berge-Thierry et al. [2003]  model is established from a European dataset combined with a few records from the western United States in the upper magnitude range and is used in  Clément et al. [2004] ,  Beauval and Scotti [2004] , and  Beauval et al. [2006b]. This model remains as the authoritative ground-motion model in the French Fundamental Safety Rule (RFS 2001-01). The Berge-Thierry et al. and Ambraseys' models are defined in terms of surface M S magnitude and are valid for earthquakes with magnitudes ≥4.
However, these models should not be used nowadays due to limitations of the database, including: (1) the lack of data from large magnitudes at close distances and from small magnitudes at large distances, (2) ground-motion variability was underestimated, and (3) instrumented sites were very poorly characterized and the site classes used were too simplistic. Marin et al. [2004]  and  Secanell et al. [2008]  favor the use of local data to establish a ground-motion model in M L (LDG magnitude). Marin et al. [2004]  predicts ground motions with an in-house model that relies only on French data (14 earthquakes with 2. 6 ≤ M L ≤ 5. 6; horizontal PGAs inferred from vertical velocimeters). One advantage is that the definition of magnitude in the ground-motion model is consistent with the magnitude of the earthquake catalog.
Possible drawbacks include a potential underestimation of ground-motion variability (i. e. , restricted number of earthquakes) and use of poorly constrained amplitudes outside dataset validity limits. In a project focused on the Pyrenees,  Secanell et al. [2008]  use the  Tapia et al. [2007]  ground-motion equation, which is based on a western Mediterranean dataset that includes nine events in the Pyrenees. The model is combined with the Ambraseys  [1995]  and  Ambraseys et al. [1996]  equations for magnitudes ≥ M L 5. 0. In the most recent studies, all selected groundmotion models are in terms of moment magnitude. They rely on different databases and functional forms and are selected to populate a logic tree aimed at covering the epistemic uncertainty in the area of interest. One way to select the model is to quantify its ability to predict the available local data [e.
g. ,  Delavaud et al. , 2012]. Beauval et al. [2012]  compared the predictions of a set of models available at the time with amplitudes from low-magnitude ground motions recorded in France by the RAP-RESIF network. Although models best adapted to this dataset were identified, the study showed that extrapolating results to moderate-to-large magnitude ground motions is not straightforward. In PSHA studies published since 2017, at least one model has been selected from the next generation attenuation (NGA) projects based on global data and data from the western United States [e. g. , the model of  Boore and Atkinson, 2008 in Chartier et al. , 2017a , or the model of  Abrahamson et al. , 2014 in Drouet et al. , 2020]. Some studies select a model established by the European and Middle East RESORCE database  [Akkar et al.
, 2014b ] [e. g. ,  Akkar et al. , 2014a in Martin et al. , 2017 , Bindi et al. , 2014 in Beauval et al. , 2020]. Most studies also include a global model enriched with Japanese data, [i. e. ,  Cauzzi and Faccioli, 2008 in Chartier et al. , 2017a , Cauzzi et al. , 2015 in Drouet et al. , 2020]. The exact list of models used in each study is indicated in Supplementary Table  1. The authors choose a minimum magnitude for hazard calculations that is larger or equal to the magnitude validity limit of these models [e. g. , M w 5. 0 in  Chartier et al. , 2017a ; M w 4. 5 in  Martin et al. , 2017 , Drouet et al. , 2020 , and Beauval et al. , 2020]. Martin et al. [2017]  and  Drouet et al. [2020]  are the first hazard studies to use ground-motion models in M w that use French recordings and are specifically established for the French context: (1) the  Ameri [2014]  model, calibrated on a European database, including French low-magnitude recordings, and (2) the  Drouet and Cotton [2015]  stochastic model parameterized with low-magnitude events from the Alps.
Both PSHA studies attribute a weight of 50% to these French models. Use of these existing, small-tomoderate magnitude events to tune ground-motion models developed from broad datasets [e. g. ,  Kotha et al. , 2020]  will be optimized by ongoing efforts to (1) build a ground-motion database with controlled metadata  [Traversa et al. , 2020]  and (2) to characterize recording stations with reliable and quantitative site metadata  [Hollender et al. , 2018].
The reasoning behind this is not well-documented, but  Rothé [1967]  briefly mentions the long recurrence times of significant events and the very old age of the orogenic episodes in this area. 4. 1. 2. Zonation for the  PS92 French Standard [PS92, 1995]  The next zonation update was performed by BRGM  [Despeyroux and Godefroy, 1986 ; Figure  7  left] and benefitted from drastic improvements in historical seismicity knowledge provided by the nuclear program. This update followed a well-documented methodology to establish a four-zone zonation map (0, negligible; Ia and Ib, weak seismicity; II, moderate seismicity). The approach followed was partly statistical. A catalog of macroseismic epicenters (I 0 ) was built from the SIRENE historical database and complemented with epicenters ≤100 km from the borders.
, 2004] , which was later summarized in  Bard [2011]  for teaching purposes. The seismic hazard study used two alternate seismogenic source models: the original EPAS model with 52 area sources  [Autran et al. , 1998; see Section 3. 3 ] and an aggregated version with 25 sources. A smoothed seismicity model was also derived from the earthquake catalog, with 20% weight in the final logic tree. The earthquake catalog merged a historical part based on the SisFrance macroseismic database with the instrumental LDG catalog. In the historical period, the magnitudes M L were estimated from epicentral intensities using the equation from  Levret et al. [1996]. The solutions for 140 earthquakes from  Levret et al. [1996]  were included. This national catalog was completed with relevant crossborder events from neighboring countries.
6 m/s 2 ). All other cities are either slightly or significantly above the recent PSHA studies; zone Z3 (1. 1 m/s 2 ) in Strasbourg, Clermont-Ferrand, Nantes, and Le Teil; zone Z2 (0. 7 m/s 2 ) in Rambervillers. For these cities, a clear decreasing trend can be observed when comparing results from 2002 with the three recent studies. One ex-planation for this decreasing trend might be improvements in strong-motion databases and the resulting ground-motion models, with increasing data from weak to moderate events, predicting lower ground motions for moderate events that control hazard at the 475-year return period. Another explanation might be related to the improved consistency of the magnitude in ground-motion databases and earthquake catalogs:  Martin et al. [2002]  had to assume equivalency between magnitudes M L and M S.