Multilingual Transformer Encoders: a Word-Level Task-Agnostic Evaluation

Some Transformer-based models can perform cross-lingual transfer learning: those models can be trained on a specific task in one language and give relatively good results on the same task in another language, despite having been pre-trained on monolingual tasks only. But, there is no consensus yet on whether those transformer-based models learn universal patterns across languages. We propose a word-level task-agnostic method to evaluate the alignment of contextualized representations built by such models. We show that our method provides more accurate translated word pairs than previous methods to evaluate word-level alignment. And our results show that some inner layers of multilingual Transformer-based models outperform other explicitly aligned representations, and even more so according to a stricter definition of multilingual alignment.Comment: accepted at IJCNN 202

Modelling relations with prototypes for visual relation detection

International audienceRelations between objects drive our understanding of images. Modelling them poses several challenges due to the combinatorial nature of the problem and the complex structure of natural language. This paper tackles the task of predicting relationships in the form of (subject, relation, object) triplets from still images. To address these issues, we propose a framework for learning relation prototypes that aims to capture the complex nature of relation distributions. Concurrently, a network is trained to define a space in which relationship triplets with similar spatial layouts, interacting objects and relations are clustered together. Finally, the network is compared to two models explicitly tackling the problem of synonymy among relations. For this, two well known scene-graph labelling benchmarks are used for training and testing: VRD and Visual Genome. Prediction of relations based on distance to prototype provides a significant increase in the diversity of predicted relations, improving the average relation recall from 40.3% to 41.7% on the first and 31.3% to 35.4% on the second

VISUAL RELATIONSHIP DETECTION BASED ON GUIDED PROPOSALS AND SEMANTIC KNOWLEDGE DISTILLATION

International audienceA thorough comprehension of image content demands a complex grasp of the interactions that may occur in the natural world. One of the key issues is to describe the visual relationships between objects. When dealing with real world data, capturing these very diverse interactions is a difficult problem. It can be alleviated by incorporating common sense in a network. For this, we propose a framework that makes use of semantic knowledge and estimates the relevance of object pairs during both training and test phases. Extracted from precomputed models and training annotations, this information is distilled into the neural network dedicated to this task. Using this approach, we observe a significant improvement on all classes of Visual Genome, a challenging visual relationship dataset. A 68.5% relative gain on the recall at 100 is directly related to the relevance estimate and a 32.7% gain to the knowledge distillation

Poly(3,4-ethylenedioxythiophene)-containing semi-interpenetrating polymer networks: a versatile concept for the design of optical or mechanical electroactive devices

International audienceThe synthesis of one-piece electronic conducting interpenetrating polymer networks is proposed as an alternative to multilayer architectures for the design of electroactive devices. The electronic conducting polymer poly(3,4-ethylenedioxythiophene) (PEDOT) as active component was symmetrically distributed in a solid polymer electrolyte (SPE) matrix based on poly(ethylene oxide) which was subsequently swollen with either LiClO4 or an ionic liquid. Depending on the composition and the crosslinking density of the SPEs, the ionic conductivities vary between 0.9 × 10−3 and 2.2 × 10−3 S cm−1 at 30 °C. Controlling the PEDOT content from 0.3 to 12 wt% in the material, electrochromic, electroemissive or electromechanical properties are obtained. Typical transmissive and reflective contrast values reach 33 and 27% at 630 and 2500 nm, respectively, for free-standing films upon application of a 1.2 V bias voltage. Both bending and linear actuating devices were developed as beam-shaped or hollow fibres. The actuation occurs under low applied voltage up to 4 V and the output force ranges from 50 to 300 mN. In all cases the electroactive properties are stable over 10 000 (electroemissivity) to 3.5 × 106 (actuation) cycles in open air providing an ionic liquid is used as electrolyte

Development of sensitive and robust multiplex digital PCR assays for the detection of ESR1 mutations in the plasma of metastatic breast cancer patients

International audienceBACKGROUND: Early detection of ESR1 mutations is a key element for better personalization of the management of patients with HR+/HER2- Metastatic Breast Cancer (MBC). Analysis of circulating tumor DNA from liquid biopsies is a particularly well-suited strategy for longitudinal monitoring of such patients. MATERIALS AND METHODS: Using the naica® three-color digital PCR platform, we developed a screening assay allowing the detection of 11 ESR1 mutations and designed a sequential strategy for precise mutation identification. We then applied this strategy in the analysis of plasma circulating cell-free DNA from 109 HR+/HER2- MBC patients and performed a double-blind comparison study on a subset of patients with the multiplex assay used at the Institut Curie (IC) for the PADA-1 study. RESULTS: Thirty-one patients (28.4%) harboured at least one ESR1 mutation, with the following frequencies: D538G (41.03%), Y537S (25.64%), E380Q (10.26%), Y537N (10.26%), "(536-540)" (7.69%), Y537C (2.56%), and L536R (2.56%). The presence of ESR1 mutation(s) was significantly associated with liver metastases (p = 0.0091). A very good agreement (91%) was observed with the IC assay. CONCLUSION: Our assays have proven to be robust and highly sensitive and are very well-suited for monitoring ESR1 mutations in the plasma of MBC patients

Clinical, pathological, and comprehensive molecular analysis of the uterine clear cell carcinoma: a retrospective national study from TMRG and GINECO network

Abstract Background Uterine clear cell carcinomas (CCC) represent less than 5% of uterine cancers. Their biological characteristics and clinical management remain uncertain. A multicenter study to explore both clinical and molecular features of these rare tumors was conducted. Methods This multicenter retrospective national study was performed within the French TMRG (Rare Gynecologic Malignant Tumors) network. Clinical data and, when available, FFPE blocks were collected. Clinical features, treatments, and outcome (progression-free survival (PFS) and overall survival (OS)) were analyzed and correlated to the protein (tissue micro-array), RNA (Nanostring nCounter® technology), and DNA (array-Comparative Genomic hybridization and target-next generation sequencing) levels using the tumor samples available. Results Sixty-eight patients with uterine CCC were enrolled, 61 from endometrial localization and 5 with cervix localization. Median age at diagnosis was 68.9 years old (range 19–89.7). Most tumors were diagnosed at an early stage (78% FIGO stage I–II). Hysterectomy (performed in 90%) and lymph node dissection (80%) were the most frequent surgical treatment. More than 70% of patients received external beam radiotherapy and 57% received brachytherapy. Nearly half (46%) of the patients received chemotherapy. After a median follow-up of 24.7 months, median PFS was 64.8 months (95 CI [5.3–124.4]) and median OS was 79.7 (IC95 [31.0–128.4]). Low hormone receptor expression (13% estrogen-receptor positive), frequent PI3K pathway alterations (58% PTEN loss, 50% PIK3CA mutations), and P53 abnormalities (41%) were observed. Mismatch repair deficiency was identified in 20%. P16 expression was associated with shorter PFS (HR = 5.88, 95 CI [1.56–25], p = 0.009). Transcriptomic analyzes revealed a specific transcriptomic profile notably with a high expression of immune response-associated genes in uterine CCC displaying a very good overall prognosis. Conclusions Uterine CCC reported to be potentially MSI high, hormone receptors negative, and sometimes TP53 mutated. However, some patients with immune response-associated features and better prognosis may be candidate to treatment de-escalation and immunotherapy

Structural and chemical transformations induced by laser impact on TiO2 and Nb2O5

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