Add new paper

alanakbik · Jan 24, 2025 · 1a61de7 · 1a61de7
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diff --git a/content/LatestNews.tsx b/content/LatestNews.tsx
@@ -29,6 +29,15 @@ import type { PinnedMessage, TimelineEntryData } from "@/content/types";
  */
 
 const LatestNews: TimelineEntryData[] = [
+    {
+        date: "2025-01-25",
+        category: "Paper accepted",
+        conference: "NAACL 2025",
+        content: <>
+            Our paper &quot;Familarity: Better Evaluation of Zero-Shot Named Entity Recognition by Quantifying Label Shifts in Synthetic Training Data&quot;
+            accepted to <InlineLink href="https://arxiv.org/abs/2412.10121" target="_blank">NAACL 2025</InlineLink> (main conference)!
+        </>,
+    },
     {
         date: "2024-12-05",
         category: "New Model",

diff --git a/content/Publications.ts b/content/Publications.ts
@@ -6,6 +6,14 @@
 import type { Publication } from "@/content/types";
 
 const Publications: Publication[] = [
+    {
+        year: 2025,
+        conference: "NAACL 2025",
+        title: "Familarity: Better Evaluation of Zero-Shot Named Entity Recognition by Quantifying Label Shifts in Synthetic Training Data",
+        authors: "Jonas Golde, Patrick Haller, Max Ploner, Fabio Barth, Nicolaas Jedema and Alan Akbik",
+        footnote: "Proceedings of the 2025 Annual Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics",
+        links: [{ label: "PDF", url: "https://arxiv.org/abs/2412.10121/" }],
+    },
     {
         year: 2024,
         conference: "CoNLL 2024",
@@ -83,6 +91,12 @@ const Publications: Publication[] = [
         authors: "Max Ploner and Alan Akbik",
         footnote: "Findings of the Association for Computational Linguistics: EACL 2024",
         links: [{ label: "PDF", url: "https://aclanthology.org/2024.findings-eacl.122/" }],
+    }, {
+        year: 2024,
+        title: "Don't Mesh with Me: Generating Constructive Solid Geometry Instead of Meshes by Fine-Tuning a Code-Generation LLM",
+        authors: "Maximilian Mews, Ansar Aynetdinov, Vivian Schiller, Peter Eisert and Alan Akbik",
+        links: [{ label: "PDF", url: "https://arxiv.org/abs/2411.15279" }],
+        footnote: "arXiv preprint",
     }, {
         year: 2024,
         title: "TransformerRanker: A Tool for Efficiently Finding the Best-Suited Language Models for Downstream Classification Tasks",