Use trajectories_with_cognitive_map_probe_examples dataset

Load trajectories with probe predictions from project-telos/trajectories_with_cognitive_map_probe_examples,
with pre/post-reasoning, size (7/11/15), complexity, and index selectors.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

README.md

@@ -10,7 +10,7 @@ license: apache-2.0
 
 Interactive trace viewer for visualizing language model agent trajectories in 2D grid environments, with probing results overlaid on tokens.
 
-Trajectories can be loaded directly from the [project-telos/trajectories_test_full](https://huggingface.co/datasets/project-telos/trajectories_test_full) dataset, or uploaded as JSON files (e.g. from [project-telos/trajectories_test_full_with_cognitive_map_probes](https://huggingface.co/datasets/project-telos/trajectories_test_full_with_cognitive_map_probes) for probe visualizations).
+Trajectories with probe predictions can be loaded directly from the [project-telos/trajectories_with_cognitive_map_probe_examples](https://huggingface.co/datasets/project-telos/trajectories_with_cognitive_map_probe_examples) dataset, or uploaded as JSON files.
 
 Part of the paper: [A Behavioural and Representational Evaluation of Goal-Directedness in Language Model Agents](https://arxiv.org/abs/2602.08964).
 

index.html

@@ -750,12 +750,15 @@
             <div class="controls">
                 <div class="hf-loader">
                     <span class="hf-icon">🤗</span>
+                    <label>Probes:</label>
+                    <select id="hfProbeType">
+                        <option value="pre_reasoning">Pre-reasoning</option>
+                        <option value="post_reasoning">Post-reasoning</option>
+                    </select>
                     <label>Size:</label>
                     <select id="hfSize">
                         <option value="7">7</option>
-                        <option value="9">9</option>
                         <option value="11">11</option>
-                        <option value="13">13</option>
                         <option value="15">15</option>
                     </select>
                     <label>Complexity:</label>
@@ -881,6 +884,7 @@
         const helpHeader = document.getElementById('helpHeader');
         const helpContent = document.getElementById('helpContent');
         const layerSelector = document.getElementById('layerSelector');
+        const hfProbeType = document.getElementById('hfProbeType');
         const hfSize = document.getElementById('hfSize');
         const hfComplexity = document.getElementById('hfComplexity');
         const hfIndex = document.getElementById('hfIndex');
@@ -1019,11 +1023,12 @@
         });
 
         hfLoadBtn.addEventListener('click', async () => {
+            const probeType = hfProbeType.value;
             const size = hfSize.value;
             const comp = hfComplexity.value;
             const idx = hfIndex.value;
             const fileName = `together_ai_openai_gpt-oss-20b_size${size}_comp${comp}_${idx}.json`;
-            const url = `https://huggingface.co/datasets/project-telos/trajectories_test_full/resolve/main/size${size}/${fileName}`;
+            const url = `https://huggingface.co/datasets/project-telos/trajectories_with_cognitive_map_probe_examples/resolve/main/${probeType}/size${size}/${fileName}`;
 
             hfLoadBtn.disabled = true;
             hfLoadBtn.textContent = 'Loading...';
@@ -1033,7 +1038,8 @@
                     throw new Error(`Failed to fetch trajectory (${response.status})`);
                 }
                 const data = await response.json();
-                loadTrajectoryData(data, `s${size}_c${comp}_${idx}`);
+                const shortProbe = probeType === 'pre_reasoning' ? 'pre' : 'post';
+                loadTrajectoryData(data, `${shortProbe}_s${size}_c${comp}_${idx}`);
             } catch (error) {
                 alert('Error loading from HuggingFace: ' + error.message);
                 console.error(error);