Run step
Step 9: assistant
thinking
Calls code_execution
{
"code": "import json\nfor q in [\"Kantamneni Engels \\\"Are Sparse Autoencoders Useful\\\" response SAE probing baseline\",\"SAE probes attention probe baseline multi-token outperform 2025 follow-up\"]:\n r=await web_search({\"query\":q})\n for x in r[:6]:\n print(x.get('title'),x.get('url'),(x.get('content') or '')[:300].replace('\\n',' '))\n print('---')"
}Calls web_search
{
"query": "Kantamneni Engels \"Are Sparse Autoencoders Useful\" response SAE probing baseline"
}web_search_tool_result
{
"type": "web_search_tool_result",
"caller": {
"type": "code_execution_20260120",
"tool_id": "srvtoolu_01Kk8bsiusTgvggWAMDxMY3h"
},
"content": [
{
"url": "https://arxiv.org/html/2610.20139",
"type": "web_search_result",
"title": "Sparse Autoencoders for Mechanistic Interpretability in NLP:A Critical Survey of Recoverability, Interpretability, and Utility",
"page_age": null,
"encrypted_content": "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"
},
{
"url": "https://openreview.net/forum?id=rNfzT8YkgO",
"type": "web_search_result",
"title": "Are Sparse Autoencoders Useful? A Case Study in Sparse Probing",
"page_age": "515 days ago",
"encrypted_content": "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"
},
{
"url": "https://proceedings.mlr.press/v267/kantamneni25a.html",
"type": "web_search_result",
"title": "Are Sparse Autoencoders Useful? A Case Study in Sparse Probing",
"page_age": "405 days ago",
"encrypted_content": "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"
},
{
"url": "https://arxiv.org/pdf/2506.23845",
"type": "web_search_result",
"title": "Use Sparse Autoencoders to Discover Unknown Concepts, ...",
"page_age": null,
"encrypted_content": "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"
},
{
"url": "https://medium.com/@namanlazarus/do-sparse-dictionary-learning-methods-actually-help-extending-the-case-study-beyond-saes-e5b883e50e4f",
"type": "web_search_result",
"title": "Do Sparse Dictionary Learning Methods Actually Help? Extending the Case Study Beyond SAEs",
"page_age": "195 days ago",
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},
{
"url": "https://arxiv.org/html/2506.23845",
"type": "web_search_result",
"title": "Position: Use Sparse Autoencoders to Discover Unknowns",
"page_age": "133 days ago",
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{
"url": "https://www.researchgate.net/publication/389315006_Are_Sparse_Autoencoders_Useful_A_Case_Study_in_Sparse_Probing",
"type": "web_search_result",
"title": "(PDF) Are Sparse Autoencoders Useful? A Case Study in Sparse Probing",
"page_age": "630 days ago",
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{
"url": "https://arxiv.org/pdf/2602.14687",
"type": "web_search_result",
"title": "SynthSAEBench: Evaluating Sparse Autoencoders on Scalable Realistic Synthetic Data",
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{
"url": "https://arxiv.org/pdf/2502.16681",
"type": "web_search_result",
"title": "Are Sparse Autoencoders Useful? A Case Study in Sparse Probing",
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},
{
"url": "https://arxiv.org/pdf/2602.14111",
"type": "web_search_result",
"title": "Sanity Checks for Sparse Autoencoders: Do SAEs Beat Random Baselines?",
"page_age": null,
"encrypted_content": "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"
}
],
"tool_use_id": "srvtoolu_01Y8nj1AqYsbGH26waDXYcfe"
}code_execution_tool_result
{
"type": "code_execution_tool_result",
"content": {
"type": "encrypted_code_execution_result",
"stderr": "Traceback (most recent call last):\n File \"/usr/local/lib/python3.11/asyncio/runners.py\", line 190, in run\n return runner.run(main)\n ^^^^^^^^^^^^^^^^\n File \"/usr/local/lib/python3.11/asyncio/runners.py\", line 118, in run\n return self._loop.run_until_complete(task)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/usr/local/lib/python3.11/asyncio/base_events.py\", line 654, in run_until_complete\n return future.result()\n ^^^^^^^^^^^^^^^\n File \"/tmp/srvtoolu_01Kk8bsiusTgvggWAMDxMY3h/cell.py\", line 12, in <module>\n print(x.get('title'),x.get('url'),(x.get('content') or '')[:300].replace('\\n',' '))\n ^^^^^\nAttributeError: 'str' object has no attribute 'get'\n",
"content": [],
"return_code": 1,
"encrypted_stdout": "Eo4BCioIFRgCIiRhOGFlOWMyMy1iYWVmLTRiYzctOWJjYS04YTM3MTE5YWVhMGMSDA6ELdaRzI7Qu2EeixoMErpv7ck4yhqRKIoiIjDM065QpUyO6H4PuqPUa+yH+RpqnkDFP6nc3DTUGsKU+nv0sMieKGtVkRBxiNdRWnkqEt5WoxHwerFBIa3oBVemaq1+JRgD"
},
"tool_use_id": "srvtoolu_01Kk8bsiusTgvggWAMDxMY3h"
}Calls code_execution
{
"code": "for q in [\"Kantamneni Engels \\\"Are Sparse Autoencoders Useful\\\" response SAE probing baseline\",\"SAE probes attention probe baseline multi-token outperform 2025 follow-up\"]:\n r=await web_search({\"query\":q})\n if isinstance(r,str): r=json.loads(r)\n for x in r[:6]:\n if isinstance(x,dict): print(x.get('title'),x.get('url'),(x.get('content') or '')[:300].replace('\\n',' '))\n else: print(str(x)[:300])\n print('---')"
}Calls web_search
{
"query": "Kantamneni Engels \"Are Sparse Autoencoders Useful\" response SAE probing baseline"
}web_search_tool_result
{
"type": "web_search_tool_result",
"caller": {
"type": "code_execution_20260120",
"tool_id": "srvtoolu_014yQTY6pUWsQXvzFfpQypom"
},
"content": [
{
"url": "https://arxiv.org/html/2610.20139",
"type": "web_search_result",
"title": "Sparse Autoencoders for Mechanistic Interpretability in NLP:A Critical Survey of Recoverability, Interpretability, and Utility",
"page_age": null,
"encrypted_content": "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"
},
{
"url": "https://openreview.net/forum?id=rNfzT8YkgO",
"type": "web_search_result",
"title": "Are Sparse Autoencoders Useful? A Case Study in Sparse Probing",
"page_age": "515 days ago",
"encrypted_content": "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"
},
{
"url": "https://proceedings.mlr.press/v267/kantamneni25a.html",
"type": "web_search_result",
"title": "Are Sparse Autoencoders Useful? A Case Study in Sparse Probing",
"page_age": "405 days ago",
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"url": "https://arxiv.org/pdf/2506.23845",
"type": "web_search_result",
"title": "Use Sparse Autoencoders to Discover Unknown Concepts, ...",
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{
"url": "https://medium.com/@namanlazarus/do-sparse-dictionary-learning-methods-actually-help-extending-the-case-study-beyond-saes-e5b883e50e4f",
"type": "web_search_result",
"title": "Do Sparse Dictionary Learning Methods Actually Help? Extending the Case Study Beyond SAEs",
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"url": "https://arxiv.org/html/2506.23845",
"type": "web_search_result",
"title": "Position: Use Sparse Autoencoders to Discover Unknowns",
"page_age": "133 days ago",
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{
"url": "https://www.researchgate.net/publication/389315006_Are_Sparse_Autoencoders_Useful_A_Case_Study_in_Sparse_Probing",
"type": "web_search_result",
"title": "(PDF) Are Sparse Autoencoders Useful? A Case Study in Sparse Probing",
"page_age": "630 days ago",
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},
{
"url": "https://arxiv.org/pdf/2602.14687",
"type": "web_search_result",
"title": "SynthSAEBench: Evaluating Sparse Autoencoders on Scalable Realistic Synthetic Data",
"page_age": null,
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},
{
"url": "https://arxiv.org/pdf/2502.16681",
"type": "web_search_result",
"title": "Are Sparse Autoencoders Useful? A Case Study in Sparse Probing",
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},
{
"url": "https://arxiv.org/pdf/2602.14111",
"type": "web_search_result",
"title": "Sanity Checks for Sparse Autoencoders: Do SAEs Beat Random Baselines?",
"page_age": null,
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}
],
"tool_use_id": "srvtoolu_0184T6amHRE8AcEXqq3vM8jZ"
}Calls web_search
{
"query": "SAE probes attention probe baseline multi-token outperform 2025 follow-up"
}web_search_tool_result
{
"type": "web_search_tool_result",
"caller": {
"type": "code_execution_20260120",
"tool_id": "srvtoolu_014yQTY6pUWsQXvzFfpQypom"
},
"content": [
{
"url": "https://arxiv.org/pdf/2502.16681",
"type": "web_search_result",
"title": "Are Sparse Autoencoders Useful? A Case Study in Sparse Probing",
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"url": "https://www.greaterwrong.com/posts/NMLq8yoTecAF44KX9/sae-probing-what-is-it-good-for-absolutely-something",
"type": "web_search_result",
"title": "SAE Probing: What is it good for? - LessWrong 2.0 viewer",
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{
"url": "https://www.alignmentforum.org/posts/osNKnwiJWHxDYvQTD/takeaways-from-our-recent-work-on-sae-probing",
"type": "web_search_result",
"title": "Takeaways From Our Recent Work on SAE Probing — AI Alignment Forum",
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{
"url": "https://arxiv.org/html/2504.20271",
"type": "web_search_result",
"title": "Investigating task-specific prompts and sparse autoencoders for activation monitoring",
"page_age": "565 days ago",
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{
"url": "https://arxiv.org/html/2506.10805v1",
"type": "web_search_result",
"title": "Detecting High-Stakes Interactions with Activation Probes",
"page_age": "520 days ago",
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"url": "https://arxiv.org/pdf/2504.20271",
"type": "web_search_result",
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{
"url": "https://arxiv.org/pdf/2608.27397",
"type": "web_search_result",
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{
"url": "https://www.goodfire.com/research/rakuten-sae-probes-for-pii-detection",
"type": "web_search_result",
"title": "Deploying Interpretability to Production with Rakuten: SAE Probes for PII Detection",
"page_age": "383 days ago",
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{
"url": "https://medium.com/@namanlazarus/do-sparse-dictionary-learning-methods-actually-help-extending-the-case-study-beyond-saes-e5b883e50e4f",
"type": "web_search_result",
"title": "Do Sparse Dictionary Learning Methods Actually Help? Extending the Case Study Beyond SAEs",
"page_age": "195 days ago",
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}
],
"tool_use_id": "srvtoolu_015dfvAudmzUyP55HtmLwsEB"
}code_execution_tool_result
{
"type": "code_execution_tool_result",
"content": {
"type": "encrypted_code_execution_result",
"stderr": "",
"content": [],
"return_code": 0,
"encrypted_stdout": 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"
},
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}thinking
Calls add_argument
{
"name": "The argument from the within-study baseline reruns",
"stance": "for",
"claim_id": "738d9786-0b87-4b75-9c33-cabe43c903d5",
"description": "Kantamneni et al. reran each SAE-favourable case study with a dense baseline (logistic regression, attention-pooled probe) and got comparable results."
}Calls add_argument
{
"name": "The argument from residual SAE advantages and hindsight baselines",
"stance": "against",
"claim_id": "738d9786-0b87-4b75-9c33-cabe43c903d5",
"description": "In the same study the SAE latent still beat the baseline on mislabeled CoLA examples, SAE probes still won some pooled comparisons, and the baseline routes to the spurious-feature finding were run after SAEs had pointed to it."
}