Added author page for Diogo Silva

data/xml/2022.wassa.xml

@@ -449,7 +449,7 @@
     </paper>
     <paper id="34">
       <title>Polite Task-oriented Dialog Agents: To Generate or to Rewrite?</title>
-      <author><first>Diogo</first><last>Silva</last></author>
+      <author id="diogo-silva-nova"><first>Diogo</first><last>Silva</last></author>
       <author><first>David</first><last>Semedo</last></author>
       <author><first>João</first><last>Magalhães</last></author>
       <pages>304-314</pages>

data/xml/2024.acl.xml

@@ -9658,7 +9658,7 @@
       <author><first>João</first><last>Bordalo</last><affiliation>NOVA School of Science and Technology</affiliation></author>
       <author><first>Vasco</first><last>Ramos</last></author>
       <author><first>Rodrigo</first><last>Valério</last></author>
-      <author><first>Diogo</first><last>Glória-Silva</last><affiliation>Universidade NOVA de Lisboa</affiliation></author>
+      <author id="diogo-silva-nova"><first>Diogo</first><last>Glória-Silva</last><affiliation>Universidade NOVA de Lisboa</affiliation></author>
       <author><first>Yonatan</first><last>Bitton</last><affiliation>Google</affiliation></author>
       <author><first>Michal</first><last>Yarom</last><affiliation>Research, Google</affiliation></author>
       <author><first>Idan</first><last>Szpektor</last><affiliation>Google</affiliation></author>

data/xml/2024.eacl.xml

@@ -1054,7 +1054,7 @@
     </paper>
     <paper id="77">
       <title>Plan-Grounded Large Language Models for Dual Goal Conversational Settings</title>
-      <author orcid="0000-0002-4420-7455"><first>Diogo</first><last>Glória-Silva</last><affiliation>Universidade NOVA de Lisboa</affiliation></author>
+      <author orcid="0000-0002-4420-7455" id="diogo-silva-nova"><first>Diogo</first><last>Glória-Silva</last><affiliation>Universidade NOVA de Lisboa</affiliation></author>
       <author><first>Rafael</first><last>Ferreira</last><affiliation>Universidade NOVA de Lisboa</affiliation></author>
       <author><first>Diogo</first><last>Tavares</last><affiliation>Universidade NOVA de Lisboa</affiliation></author>
       <author><first>David</first><last>Semedo</last><affiliation>Universidade NOVA de Lisboa and Universidade NOVA de Lisboa</affiliation></author>

data/xml/2024.emnlp.xml

@@ -16421,7 +16421,7 @@
     </paper>
     <paper id="1191">
       <title>Show and Guide: Instructional-Plan Grounded Vision and Language Model</title>
-      <author orcid="0000-0002-4420-7455"><first>Diogo</first><last>Glória-Silva</last><affiliation>Universidade NOVA de Lisboa</affiliation></author>
+      <author orcid="0000-0002-4420-7455" id="diogo-silva-nova"><first>Diogo</first><last>Glória-Silva</last><affiliation>Universidade NOVA de Lisboa</affiliation></author>
       <author><first>David</first><last>Semedo</last><affiliation>Universidade NOVA de Lisboa and Universidade NOVA de Lisboa</affiliation></author>
       <author><first>Joao</first><last>Magalhaes</last><affiliation>Universidade Nova de Lisboa</affiliation></author>
       <pages>21371-21389</pages>

data/xml/2025.semeval.xml

@@ -3218,7 +3218,7 @@
       <author><first>Julia S.</first><last>Dollis</last></author>
       <author><first>Daniel M.</first><last>Pedrozo</last></author>
       <author><first>Artur M. A.</first><last>Novais</last></author>
-      <author><first>Diogo F. C.</first><last>Silva</last></author>
+      <author id="diogo-silva"><first>Diogo F. C.</first><last>Silva</last></author>
       <author><first>Arlindo R.</first><last>Galvão Filho</last></author>
       <pages>2305-2310</pages>
       <abstract>This paper investigates the impact of data quality and processing strategies on emotion recognition in Brazilian Portuguese (PTBR) texts. We focus on data distribution, linguistic context, and augmentation techniques such as translation and synthetic data generation. To evaluate these aspects, we conduct experiments on the PTBR portion of the BRIGHTER dataset, a manually curated multilingual dataset containing nearly 100,000 samples, of which 4,552 are in PTBR. Our study encompasses both multi-label emotion detection (presence/absence classification) and emotion intensity prediction (0 to 3 scale), following the SemEval 2025 Track 11 setup. Results demonstrate that emotion intensity labels enhance model performance after discretization, and that smaller multilingual models can outperform larger ones in low-resource settings. Our official submission ranked 6th, but further refinements improved our ranking to 3rd, trailing the top submission by only 0.047, reinforcing the significance of a data-centric approach in emotion recognition.</abstract>

data/yaml/name_variants.yaml

@@ -919,6 +919,16 @@
 - canonical: {first: Hatte, last: Blejer}
   variants:
   - {first: Hatte R., last: Blejer}
+- canonical: {first: Diogo, last: Glória-Silva}
+  variants:
+  - {first: Diogo, last: Silva}
+  id: diogo-silva-nova
+  orcid: 0000-0002-4420-7455
+  institution: NOVA University of Lisbon, School of Science and Technology
+  comment: NOVA
+- canonical: {first: Diogo, last: Glória-Silva}
+  id: diogo-silva
+  comment: May refer to several people
 - canonical: {first: André, last: Blessing}
   variants:
   - {first: Andre, last: Blessing}