.

Author: Mountlex

public/content/about.md

@@ -1,57 +1,18 @@
 ---
-title: 'About'
-slug: '/about'
+title: "About"
+slug: "/about"
 ---
 
 ## About
 
-This website aims to collect and organize research papers on **algorithms with predictions** (also known as **algorithms with machine learning advice** or **learning-augmented algorithms**).
+The goal of this project is to provide a comprehensive overview of the current state of research on Algorithms with Predictions and to curate links to further relevant materials. This resource is intended to help new researchers quickly orient themselves in the field while also serving as a valuable reference for the broader research community to organize and cluster the rapidly growing body of results and publications in this area.
 
-### What are Algorithms with Predictions?
+This project and its webpage are led and managed by [Alexander Lindermayr](https://www.alexanderlindermayr.com) and [Nicole Megow](https://www.uni-bremen.de/en/cslog/nmegow).
 
-Algorithms with predictions represent a fascinating intersection of theoretical computer science and machine learning. These algorithms leverage machine learning predictions to improve their performance beyond worst-case guarantees, while maintaining robustness when predictions are inaccurate.
+It is an [open source initiative](https://github.com/algorithms-with-predictions/algorithms-with-predictions.github.io), and contributions from the community are highly encouraged, such as submitting references or links, suggesting improvements to presentation and organization, or sharing ideas for enhancing the platform. If you have any questions or suggestions, please don’t hesitate to reach out directly to [Alexander and Nicole](mailto:[email protected]).
 
-Key characteristics include:
+Further contributors: [Bertrand Simon](https://cclab.pages.in2p3.fr/bertrand.simon/), [Adam Polak](https://adampolak.github.io/), [Niklas Hahn](https://webia.lip6.fr/~nhahn/index.html), [Christoph Dürr](https://webia.lip6.fr/~durrc/), [Ola Svensson](https://theory.epfl.ch/osven/)
 
-- **Consistency**: Good performance when predictions are accurate
-- **Robustness**: Reasonable performance when predictions are wrong  
-- **Smoothness**: Performance degrades gracefully with prediction quality
+Fortunately, the idea of this project has been picked up by other communities. The following forks of this project exist.
 
-### Research Areas
-
-This field spans multiple domains of algorithmic research:
-
-- **Online Algorithms**: Making decisions without knowing future inputs
-- **Approximation Algorithms**: Finding near-optimal solutions efficiently
-- **Streaming Algorithms**: Processing data with limited memory
-- **Data Structures**: Optimizing access patterns with predicted queries
-- **Scheduling**: Improving job scheduling with workload predictions
-- **Network Problems**: Route optimization with traffic forecasts
-
-### Community
-
-The algorithms with predictions community has grown rapidly, with dedicated workshops, conference sessions, and research groups worldwide. This website serves as a central hub for:
-
-- Paper discovery and organization
-- Research trend identification  
-- Community building
-- Educational resources
-
-### Contact
-
-For questions, suggestions, or contributions to this website:
-
-- Email: [[email protected]](mailto:[email protected])
-- GitHub: [algorithms-with-predictions organization](https://github.com/algorithms-with-predictions)
-
-### Technical Details
-
-This website is built with:
-
-- **React** and **Vite** for fast development and building
-- **Material-UI** for consistent design
-- **YAML** files for paper data management
-- **Markdown** for content pages
-- **GitHub Pages** for hosting
-
-All code is open source and contributions are welcome!
+- [Satisfiability for Mathematics](https://bsubercaseaux.github.io/sat-for-math/) created and maintained by [Bernardo Subercaseaux](https://bsubercaseaux.github.io/)

public/content/contribute.md

@@ -3,30 +3,21 @@ title: 'How to Contribute'
 slug: '/contribute'
 ---
 
-## How to Contribute in General
+## Welcome, Contributors
 
-The sources and data for this webpage are available on
-[GitHub](https://github.com/algorithms-with-predictions/algorithms-with-predictions.github.io). It
-uses modern web technologies for static site rendering and is hosted via
-[GitHub Pages](https://pages.github.com/).
+This project is open source and lives on [GitHub](https://github.com/algorithms-with-predictions/algorithms-with-predictions.github.io). We welcome all contributions.
 
-Everyone is very welcome to contribute:
+For most changes, please open a **Pull Request**. For bigger ideas or questions, you can email us at [[email protected]](mailto:[email protected]).
 
-- Maintain paper references, e.g. adding, updating and labeling references (see `papers/` directory
-  and syntax below)
-- Add and edit further material. This page is generated from markdown files and is
-  thus easy to modify.
-- Improve layout or design, add new features.
+---
 
-Most contributions can be done via Pull Requests directly in the repository. For more involved
-suggestions or discussions, feel free to contact us
-([[email protected]](mailto:[email protected])).
+## Adding or Editing Papers
 
-## Adding and Editing Paper References
+Paper data is stored as YAML files in the `papers/` directory.
 
-Paper entries are based on YAML files, which are located in the directory `papers/`.
+### Paper File Structure
 
-As an example, this is the data file for the caching paper by Lykouris and Vassilvitskii:
+Each paper is a `.yml` file. Name files descriptively (e.g., `Author21topic.yml`). Here’s a quick example:
 
 ```yaml
 title: Competitive Caching with Machine Learned Advice
@@ -38,68 +29,24 @@ publications:
 - name: ICML
   url: https://proceedings.mlr.press/v80/lykouris18a.html
   year: 2018
-  dblp_key: conf/icml/LykourisV18
-  bibtex: "@inproceedings{DBLP:conf/icml/LykourisV18,\\n  author = {Thodoris Lykouris and\\n  Sergei Vassilvitskii},\\n  title = {Competitive Caching with Machine Learned Advice},\\n  booktitle = {{ICML}},\\n  series = {Proceedings of Machine Learning Research},\\n  volume = {80},\\n  pages = {3302--3311},\\n  publisher = {{PMLR}},\\n  year = {2018}\\n}\\n"
+  dblp_key: conf/icml/LykourisV18 # Optional
+  bibtex: "@inproceedings{...}"   # Optional
 - name: arXiv
   url: https://arxiv.org/abs/1802.05399
   year: 2018
-  month: 2
-  day: 15
 ```
 
-### Required Fields
-
-Each paper entry must contain:
-
-- **title**: The full title of the paper
-- **authors**: List of authors (can be string or array)
-- **labels**: Categories/tags for the paper
-- **publications**: Array of publication venues
-
-### Publication Fields
-
-Each publication entry should include:
-
-- **name**: Venue name (conference, journal, or "arXiv")
-- **url**: Direct link to the paper
-- **year**: Publication year
-- **dblp_key**: (optional) DBLP key for the entry
-- **bibtex**: (optional) BibTeX citation
-
-### Labels/Categories
+### Key Fields
 
-Use consistent labels to help with filtering:
+- **`title`**: Full paper title.
+- **`authors`**: Author names.
+- **`labels`**: A list of relevant categories (see below for common labels).
+- **`publications`**: List of venues, each with a `name`, `url`, and `year`.
 
-- `online` - Online algorithms
-- `caching / paging` - Caching and paging problems
-- `streaming` - Streaming algorithms
-- `approximation` - Approximation algorithms
-- `game theory / mechanism design` - Game theory applications
-- `differential privacy` - Privacy-preserving algorithms
-- `survey` - Survey papers
 
-## File Naming Convention
 
-Name files descriptively based on authors and topic:
-- `AuthorName20keyword.yml`
-- `SmithJones21caching.yml`
-- `Survey23online.yml`
-
-## Testing Your Contribution
-
-Before submitting:
-
-1. Validate YAML syntax
-2. Check that all URLs work
-3. Ensure consistent formatting
-4. Test locally if possible
-
-## Content Pages
-
-You can also edit the content pages by modifying the markdown files in `public/content/`:
+---
 
-- `public/content/material.md` - Further Material page
-- `public/content/contribute.md` - How to Contribute page (this page!)
-- `public/content/about.md` - About page
+## Editing Website Content
 
-These files use standard markdown with YAML frontmatter for metadata.
+You can edit the site's informational pages by modifying the markdown files in `public/content/`, such as `about.md` or this very file.

src/components/header.jsx

@@ -67,6 +67,7 @@ const Header = () => {
                 borderRadius: 2,
                 color: 'white !important',
                 textDecoration: 'none !important',
+                fontSize: '1.1rem',
                 '&:hover': {
                   backgroundColor: 'rgba(255, 255, 255, 0.1)',
                   transform: 'translateY(-1px)',
@@ -130,7 +131,7 @@ const Header = () => {
                   '&:visited': {
                     color: 'white !important',
                   },
-                  fontSize: '0.95rem',
+                  fontSize: '1rem',
                   fontWeight: 500,
                 }}
               >

src/components/paperlist.jsx

@@ -8,7 +8,7 @@ import {
   Tooltip,
   Chip,
 } from '@mui/material';
-import { Download } from '@mui/icons-material';
+import { Download, Clear } from '@mui/icons-material';
 import * as React from 'react';
 import { useState, useMemo } from 'react';
 import PropTypes from 'prop-types';
@@ -126,6 +126,11 @@ const PaperList = ({ data }) => {
     }
   };
 
+  const handleClearFilters = () => {
+    setSearchQuery('');
+    setSelLabels([]);
+  };
+
   const labelColor = label => {
     if (TYPE_LABELS.includes(label)) {
       return 'typeLabels';
@@ -200,62 +205,48 @@ const PaperList = ({ data }) => {
               )}
             </Typography>
 
-            {/* Export BibTeX button */}
-            {papersWithBibtex > 0 && (
-              <Tooltip
-                title={`Export BibTeX for ${papersWithBibtex} papers with bibliography`}
-              >
-                <IconButton
-                  size="small"
-                  onClick={handleExportBibtex}
-                  sx={{
-                    color: 'primary.main',
-                    '&:hover': {
-                      bgcolor: 'primary.light',
-                      color: 'primary.contrastText',
-                    },
-                  }}
-                >
-                  <Download fontSize="small" />
-                </IconButton>
-              </Tooltip>
-            )}
-          </Stack>
-
-          {/* Active filters display */}
-          {(searchQuery || selLabels.length > 0) && (
-            <Stack
-              direction="row"
-              spacing={0.5}
-              flexWrap="wrap"
-              sx={{ gap: 0.5, mb: 1 }}
-            >
-              {searchQuery && (
-                <Chip
-                  label={`"${searchQuery}"`}
-                  onDelete={() => setSearchQuery('')}
-                  size="small"
-                  color="primary"
-                  variant="outlined"
-                  sx={{ height: 24, borderRadius: 2 }}
-                />
+            <Stack direction="row" spacing={0.5}>
+              {/* Clear filters button */}
+              {(searchQuery || selLabels.length > 0) && (
+                <Tooltip title="Clear all filters">
+                  <IconButton
+                    size="small"
+                    onClick={handleClearFilters}
+                    sx={{
+                      color: 'secondary.main',
+                      '&:hover': {
+                        bgcolor: 'secondary.light',
+                        color: 'secondary.contrastText',
+                      },
+                    }}
+                  >
+                    <Clear fontSize="small" />
+                  </IconButton>
+                </Tooltip>
               )}
 
-              {selLabels.map(label => (
-                <Chip
-                  key={label}
-                  label={label}
-                  onDelete={() =>
-                    setSelLabels(prev => prev.filter(l => l !== label))
-                  }
-                  size="small"
-                  color={labelColor(label)}
-                  variant="outlined"
-                  sx={{ height: 24, borderRadius: 2 }}
-                />
-              ))}
+              {/* Export BibTeX button */}
+              {papersWithBibtex > 0 && (
+                <Tooltip
+                  title={`Export BibTeX for ${papersWithBibtex} papers with bibliography`}
+                >
+                  <IconButton
+                    size="small"
+                    onClick={handleExportBibtex}
+                    sx={{
+                      color: 'primary.main',
+                      '&:hover': {
+                        bgcolor: 'primary.light',
+                        color: 'primary.contrastText',
+                      },
+                    }}
+                  >
+                    <Download fontSize="small" />
+                  </IconButton>
+                </Tooltip>
+              )}
             </Stack>
-          )}
+          </Stack>
         </Box>
       </Fade>