Dataset Preview
The full dataset viewer is not available (click to read why). Only showing a preview of the rows.
The dataset generation failed
Error code: DatasetGenerationError
Exception: CastError
Message: Couldn't cast
call_id: string
tree: string
problem: string
option: string
role: string
obligation: string
claude_session_id: string
t0: double
t1: double
request: struct<model: string, max_tokens: int64, metadata: struct<user_id: string>, stream: bool, system: st (... 82 chars omitted)
child 0, model: string
child 1, max_tokens: int64
child 2, metadata: struct<user_id: string>
child 0, user_id: string
child 3, stream: bool
child 4, system: string
child 5, thinking: struct<type: string>
child 0, type: string
child 6, tools: string
child 7, messages: list<item: string>
child 0, item: string
chat_template_kwargs: struct<enable_thinking: bool>
child 0, enable_thinking: bool
output: struct<reasoning: string, text: string, tool_calls: list<item: struct<id: string, name: string, argu (... 201 chars omitted)
child 0, reasoning: string
child 1, text: string
child 2, tool_calls: list<item: struct<id: string, name: string, arguments: string>>
child 0, item: struct<id: string, name: string, arguments: string>
child 0, id: string
child 1, name: string
child 2, arguments: string
child 3, finish_reason: string
child 4, usage: struct<prompt_tokens: int64, total_tokens: int64, completion_tokens: int64, prompt_tokens_details: s (... 53 chars omitted)
child 0, prompt_tokens: int64
child 1, total_tokens: int64
child 2, completion_tokens: int64
child 3, prompt_tokens_details: struct<cached_tokens: int64>
child 0, cached_tokens: int64
child 4, reasoning_tokens: int64
error: null
topk: int64
logprobs: list<item: list<item: string>>
child 0, item: list<item: string>
child 0, item: string
v: null
h: string
to
{'h': Value('string'), 'v': Json(decode=True)}
because column names don't match
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1835, in _prepare_split_single
for key, table in generator:
^^^^^^^^^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 621, in wrapped
for item in generator(*args, **kwargs):
~~~~~~~~~^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 361, in _generate_tables
self._cast_table(pa_table, json_field_paths=json_field_paths),
~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
pa_table = table_cast(pa_table, self.info.features.arrow_schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2381, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2309, in cast_table_to_schema
raise CastError(
...<3 lines>...
)
datasets.table.CastError: Couldn't cast
call_id: string
tree: string
problem: string
option: string
role: string
obligation: string
claude_session_id: string
t0: double
t1: double
request: struct<model: string, max_tokens: int64, metadata: struct<user_id: string>, stream: bool, system: st (... 82 chars omitted)
child 0, model: string
child 1, max_tokens: int64
child 2, metadata: struct<user_id: string>
child 0, user_id: string
child 3, stream: bool
child 4, system: string
child 5, thinking: struct<type: string>
child 0, type: string
child 6, tools: string
child 7, messages: list<item: string>
child 0, item: string
chat_template_kwargs: struct<enable_thinking: bool>
child 0, enable_thinking: bool
output: struct<reasoning: string, text: string, tool_calls: list<item: struct<id: string, name: string, argu (... 201 chars omitted)
child 0, reasoning: string
child 1, text: string
child 2, tool_calls: list<item: struct<id: string, name: string, arguments: string>>
child 0, item: struct<id: string, name: string, arguments: string>
child 0, id: string
child 1, name: string
child 2, arguments: string
child 3, finish_reason: string
child 4, usage: struct<prompt_tokens: int64, total_tokens: int64, completion_tokens: int64, prompt_tokens_details: s (... 53 chars omitted)
child 0, prompt_tokens: int64
child 1, total_tokens: int64
child 2, completion_tokens: int64
child 3, prompt_tokens_details: struct<cached_tokens: int64>
child 0, cached_tokens: int64
child 4, reasoning_tokens: int64
error: null
topk: int64
logprobs: list<item: list<item: string>>
child 0, item: list<item: string>
child 0, item: string
v: null
h: string
to
{'h': Value('string'), 'v': Json(decode=True)}
because column names don't match
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1379, in compute_config_parquet_and_info_response
parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
~~~~~~~~~~~~~~~~~~~~~~~~~^
builder, max_dataset_size_bytes=max_dataset_size_bytes
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 956, in stream_convert_to_parquet
builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1702, in _prepare_split
for job_id, done, content in self._prepare_split_single(
~~~~~~~~~~~~~~~~~~~~~~~~~~^
gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
):
^
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1887, in _prepare_split_single
raise DatasetGenerationError("An error occurred while generating the dataset") from e
datasets.exceptions.DatasetGenerationError: An error occurred while generating the datasetNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
h string | v unknown |
|---|---|
3ac10002270a8a6f1bc0d38d | [
{
"text": "x-anthropic-billing-header: cc_version=2.1.308.4b6; cc_entrypoint=sdk-cli;",
"type": "text"
},
{
"text": "You are a Claude agent, built on Anthropic's Claude Agent SDK.",
"type": "text"
},
{
"text": "\nYou are an agent working with the user toward their goals, using your own j... |
9c7028e744edc69de7d810b4 | [
{
"description": "Launch a new agent to handle complex, multi-step tasks. Each agent type has specific capabilities and tools available to it.\n\nAvailable agent types are listed in <system-reminder> messages in the conversation.\n\nWhen using the Agent tool, specify a subagent_type to select an agent: `\"fork\... |
35666716e3e606b24f82ab22 | {
"content": [
{
"text": "<system-reminder>\nCodebase and user instructions are shown below. Be sure to adhere to these instructions. IMPORTANT: These instructions OVERRIDE any default behavior and you MUST follow them exactly as written.\n\nContents of /home/ubuntu/lot-data/runs/zyq2-imo25-p1/imo_2025_p1/.... |
d3051d6c2442b0c8e48d48dd | {
"content": [
{
"text": "# Environment\nYou have been invoked in the following environment: \n - Primary working directory: /home/ubuntu/lot-data/runs/zyq2-imo25-p1/imo_2025_p1/.hmz/lot/runs/x0003/hmz/home/envs/mirrors/lotsw-zyq2-imo25-p1-baaca6-remote-47613b20/2da410f76a93\n - Is a git repository: true\n ... |
970798d9e63fe01134a0481c | [
{
"text": "x-anthropic-billing-header: cc_version=2.1.308.4b6; cc_entrypoint=sdk-cli;",
"type": "text"
},
{
"text": "You are a Claude agent, built on Anthropic's Claude Agent SDK.",
"type": "text"
},
{
"text": "\nYou are an agent working with the user toward their goals, using your own j... |
5b9b8821987d32aa85abb7fc | {
"content": [
{
"text": "<system-reminder>\nCodebase and user instructions are shown below. Be sure to adhere to these instructions. IMPORTANT: These instructions OVERRIDE any default behavior and you MUST follow them exactly as written.\n\nContents of /home/ubuntu/lot-data/runs/zyq2-imo25-p1/imo_2025_p1/.... |
d263450fc52f7a39e7fd5358 | {
"content": [
{
"text": "# Environment\nYou have been invoked in the following environment: \n - Primary working directory: /home/ubuntu/lot-data/runs/zyq2-imo25-p1/imo_2025_p1/.hmz/lot/runs/x0001/hmz/home/envs/mirrors/lotsw-zyq2-imo25-p1-baaca6-remote-1479741c/bdc982ee1a8c\n - Is a git repository: true\n ... |
3bd4c106b7b3abfead36d18f | [
{
"text": "x-anthropic-billing-header: cc_version=2.1.308.4b6; cc_entrypoint=sdk-cli;",
"type": "text"
},
{
"text": "You are a Claude agent, built on Anthropic's Claude Agent SDK.",
"type": "text"
},
{
"text": "\nYou are an agent working with the user toward their goals, using your own j... |
c75fe32cc54d7c8fa0502fb9 | {
"content": [
{
"text": "<system-reminder>\nCodebase and user instructions are shown below. Be sure to adhere to these instructions. IMPORTANT: These instructions OVERRIDE any default behavior and you MUST follow them exactly as written.\n\nContents of /home/ubuntu/lot-data/runs/zyq2-imo25-p1/imo_2025_p1/.... |
35976323051c68eeb1d77b95 | {
"content": [
{
"text": "# Environment\nYou have been invoked in the following environment: \n - Primary working directory: /home/ubuntu/lot-data/runs/zyq2-imo25-p1/imo_2025_p1/.hmz/lot/runs/x0002/hmz/home/envs/mirrors/lotsw-zyq2-imo25-p1-baaca6-remote-02fa0ebf/c90807455c40\n - Is a git repository: true\n ... |
7374f3ef17d8cbbc86dc3439 | {
"content": "# Environment\nYou have been invoked in the following environment: \n - Primary working directory: /home/ubuntu/lot-data/runs/zyq2-imo25-p1/imo_2025_p1/.hmz/lot/runs/x0001/hmz/home/envs/mirrors/lotsw-zyq2-imo25-p1-baaca6-remote-1479741c/bdc982ee1a8c\n - Is a git repository: true\n - Additional working d... |
764b2d04e62d2cdf8da003ba | {
"content": [
{
"signature": "",
"thinking": "Let's start by reading the brief and understanding the task.\n",
"type": "thinking"
},
{
"id": "call_2452c4d90b8346acbbef23ec",
"input": {
"file_path": "/home/ubuntu/lot-data/runs/zyq2-imo25-p1/imo_2025_p1/.hmz/lot/runs/x... |
e4374c33f50e01fa4deb4cb8 | {
"content": [
{
"content": "1\t# Prove root\n2\t\n3\tThe whole tree ends at 2026-10-25T06:56Z (47h59m from now).\n4\t\n5\t## The obligation\n6\t\n7\t`root` is the whole problem: define and prove every hole of it.\n8\t\n9\t- `Submission.IMO2025P1.result`\n10\t- `Submission.IMO2025P1.answer`\n11\t\n12\tModul... |
dec6910b93590309109bf876 | {
"content": "# Environment\nYou have been invoked in the following environment: \n - Primary working directory: /home/ubuntu/lot-data/runs/zyq2-imo25-p1/imo_2025_p1/.hmz/lot/runs/x0003/hmz/home/envs/mirrors/lotsw-zyq2-imo25-p1-baaca6-remote-47613b20/2da410f76a93\n - Is a git repository: true\n - Additional working d... |
b10f20da5f6e1b2c350e17d0 | {
"content": [
{
"signature": "",
"thinking": "To understand the task, let's first read the BRIEF.md file.\n",
"type": "thinking"
},
{
"id": "call_062dfee4e2ed43099ab3d75e",
"input": {
"file_path": "/home/ubuntu/lot-data/runs/zyq2-imo25-p1/imo_2025_p1/.hmz/lot/runs/x0... |
da6ee9c9b605fcc39651159d | {
"content": [
{
"content": "1\t# Prove root\n2\t\n3\tThe whole tree ends at 2026-10-25T06:56Z (47h59m from now).\n4\t\n5\t## The obligation\n6\t\n7\t`root` is the whole problem: define and prove every hole of it.\n8\t\n9\t- `Submission.IMO2025P1.result`\n10\t- `Submission.IMO2025P1.answer`\n11\t\n12\tModul... |
66bf94505f1e2018f532a852 | {
"content": "# Environment\nYou have been invoked in the following environment: \n - Primary working directory: /home/ubuntu/lot-data/runs/zyq2-imo25-p1/imo_2025_p1/.hmz/lot/runs/x0002/hmz/home/envs/mirrors/lotsw-zyq2-imo25-p1-baaca6-remote-02fa0ebf/c90807455c40\n - Is a git repository: true\n - Additional working d... |
3d68e40f0cdf09c09f40b18b | {
"content": [
{
"signature": "",
"thinking": "Let's start by reading the brief to understand the task.\n",
"type": "thinking"
},
{
"id": "call_3d3bd79137964a7d9e711f0d",
"input": {
"file_path": "/home/ubuntu/lot-data/runs/zyq2-imo25-p1/imo_2025_p1/.hmz/lot/runs/x0002... |
9c5ac2e8eb22aa4353674c1a | {
"content": [
{
"content": "1\t# Split root into smaller obligations\n2\t\n3\tThe whole tree ends at 2026-10-25T06:56Z (47h59m from now).\n4\t\n5\t## The obligation\n6\t\n7\t`root` is the whole problem: define and prove every hole of it.\n8\t\n9\t- `Submission.IMO2025P1.result`\n10\t- `Submission.IMO2025P1... |
71535b6b75ee56ab126d2d80 | {
"content": [
{
"signature": "",
"thinking": "This is the IMO 2025 Problem 1 task. First, let's read the problem files: README.md, Challenge.lean, ChallengeDeps.lean, holes.json, config.json, and the current state of the submission.\n\nFirst, I'll run `lot sync` as instructed, and check the files.\n"... |
e8b518b7652e7fc6976f21ad | {
"content": [
{
"content": "/bin/bash: line 1: lot: command not found",
"is_error": false,
"tool_use_id": "call_3ef9fa5bb4b34ba893fa37ab",
"type": "tool_result"
},
{
"content": "AGENTS.md\nCLAUDE.md\nChallenge.lean\nChallengeDeps.lean\nPROBLEM.md\nREADME.md\nSolution.lean\nS... |
b3a5f1aa7c0e7e5a0dbcc0e5 | {
"content": [
{
"signature": "",
"thinking": "`lot` is not on PATH. Let me check where it is. It might be in a different location.\n",
"type": "thinking"
},
{
"id": "call_da6e184e6da040b9bb1b480c",
"input": {
"command": "which lot; ls /home/ubuntu/lean-runs/ 2>/dev/n... |
End of preview.
hmz-logits: IMO 2025 P1, P2, P4, P5, Qwen3.8-27B on LOT, with top-100 logprobs
Agent trajectories of the four IMO 2025 problems that Qwen3.8-27B-FP8 solved in Lean 4 on the
LOT (Lean Option Tree, hmz-prover-dev changye-lot 00dfd46, LOT 4.4) workflow, with Claude Code as the
agent harness and every model call served by Qwen. For every generated token the top-100 logprobs
(log-softmax over the vocabulary, as sglang returns them; not raw logits) were recorded at sampling time.
| Problem | Tree | Answer (checked by hand against the official one) | Root accepted | Run time* | LOT sessions | Qwen calls | Generated tokens |
|---|---|---|---|---|---|---|---|
| IMO 2025 P1 | IMO2025-P1 |
fun _ => {0, 1, 3} |
2026-10-25 00:50Z | 41.9 h | 65 | 7,357 | 18.3 M |
| IMO 2025 P2 | IMO2025-P2 |
(a proof, no answer to find) | 2026-10-26 14:12Z | 44.2 h | 34 | 6,370 | 16.8 M |
| IMO 2025 P4 | IMO2025-P4 |
{n | 6∣n ∧ 5∤n ∧ v₂(n) odd ∧ 2·v₃(n) ≥ v₂(n)+1} (= 12ᵉ·6·l, l coprime to 10) |
2026-10-24 12:26Z | 29.5 h | 32 | 2,775 | 8.8 M |
| IMO 2025 P5 | IMO2025-P5 |
({c | c > 1/√2}, {c | c < 1/√2}) (who has a winning strategy: first player, second player) |
2026-10-26 07:27Z | 37.4 h | 47 | 4,039 | 14.0 M |
* From the tree's start to root acceptance, without the 35.1 h P2 and P5 were paused (10-23 14:59Z to 10-25 02:04Z).
All four were solved by decomposition, not by one session: P4's root was split into 5 lemmas, each proved by a single session (two of them after a deeper split was started); P1 was split 12 times down to depth 4, its leaves proved one by one; P5 was split into the four strategy claims (first/second player wins or not on each side of 1/√2), two of them down to depth 4; P2 (geometry) proved its tangency step by coordinates, split down to depth 3. Each proof passed the problem's trusted checker (official comparator, Lean kernel and nanoda replay) and LOT's FINAL review.
Setup
- Statements: Joseph Myers' Lean statements of IMO 2025 (github.com/jsm28/IMOLean f6515f0118), ported from
Lean 4.35's module syntax to
import Mathlib, otherwise unchanged; Lean 4.33.0, Mathlib 6f1ef4e5.answeris a definition hole: the model had to find the answer. - Model:
Qwen/Qwen3.8-27B-FP8on one RTX PRO 6000 (sglang 0.5.22, reasoning parserqwen3, tool parserqwen3_coder), at the server's default reasoning effort (xhigh); Claude Code 2.1.308 with Qwen in every model slot, 64k output cap. - Logprobs: a relay between Claude Code and sglang ran sglang's own Anthropic adapter and called
/v1/chat/completionswithlogprobs=true, top_logprobs=100, recorded the reply and passed it on without the logprobs (verified to give the same prompts and, at temperature 0, the same outputs as the server's own/v1/messages). - LOT: one model in both slots, 2 PROVE + 1 DEC sessions at a time, split reviews and FINAL 3 h.
Layout
imo2025-qwen3.8-27b-lot/
trees.jsonl one line per tree (problem, times, counts)
<tree>/
sessions.jsonl one line per LOT session (option): role (prove/dec/aud/final), obligation,
status/reason, started/ended, Claude session ids, calls and tokens
calls/calls-<hour>.jsonl.zst one line per Qwen call (one file per hour of the run)
blobs.jsonl.zst messages, system prompts and tool lists by hash: {"h": hash, "v": value}
transcripts/<id>.jsonl Claude Code's own transcript of each session (and its subagents)
meta/ LOT's records: tree.json (obligations, splits, options), events.jsonl, ...
scripts/read_calls.py reading example
A call (calls/*.jsonl.zst):
| Field | Meaning |
|---|---|
call_id, t0, t1 |
the call and its start/end (unix seconds) |
tree, problem, option, role, obligation |
the LOT session it belongs to |
claude_session_id |
the Claude Code session (= transcripts/<id>.jsonl) |
request |
the Anthropic Messages request: messages (list of blob hashes), system, tools (blob hashes), max_tokens, thinking, metadata |
chat_template_kwargs |
what reached the chat template (enable_thinking) |
output |
reasoning (thinking text), text, tool_calls [{id, name, arguments}], finish_reason, usage |
error |
null, or why the call did not finish (e.g. {"cancelled": true} when the client went away) |
topk, logprobs |
100, and one entry per generated token (thinking, text and tool-call tokens alike): [token, logprob, [[candidate, logprob], ... 100]] |
Rebuild a call's prompt with blobs.jsonl.zst (see scripts/read_calls.py). Calls that were cut off or
cancelled are kept (with whatever was generated); len(logprobs) equals the generated token count of
every finished call.
Notes
- Paths, host names and node names inside the transcripts are those of the run's containers.
- No credentials: Claude Code ran without an Anthropic sign-in (the relay's dummy token), and the files were scanned for key-shaped strings before upload.
- Downloads last month
- 114