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2026.TA.experiments.refusal_tracing.refusal_ladder

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Cannot get the split names for the config 'default' of the dataset.

Exception:    SplitsNotFoundError
Message:      The split names could not be parsed from the dataset config.
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 286, in get_dataset_config_info
                  for split_generator in builder._split_generators(
                                         ~~~~~~~~~~~~~~~~~~~~~~~~~^
                      StreamingDownloadManager(base_path=builder.base_path, download_config=download_config)
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  )
                  ^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/harbor/harbor.py", line 171, in _split_generators
                  raise DataFilesNotFoundError("No task.toml or instruction.md files found")
              datasets.exceptions.DataFilesNotFoundError: No task.toml or instruction.md files found
              
              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/split_names.py", line 68, in compute_split_names_from_streaming_response
                  for split in get_dataset_split_names(
                               ~~~~~~~~~~~~~~~~~~~~~~~^
                      path=dataset,
                      ^^^^^^^^^^^^^
                      config_name=config,
                      ^^^^^^^^^^^^^^^^^^^
                      token=hf_token,
                      ^^^^^^^^^^^^^^^
                  )
                  ^
                File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 340, in get_dataset_split_names
                  info = get_dataset_config_info(
                      path,
                  ...<6 lines>...
                      **config_kwargs,
                  )
                File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 291, in get_dataset_config_info
                  raise SplitsNotFoundError("The split names could not be parsed from the dataset config.") from err
              datasets.inspect.SplitsNotFoundError: The split names could not be parsed from the dataset config.

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Refusal ladder: transcripts

Transcripts from the refusal-ladder evaluation of 2026-08-10. The same 93 prompts (63 strict-flip harmful HarmBench requests + 30 benign control requests) were run through a ladder of models that each carry more instruction-tuning machinery, all rendered with the identical gemma-2-2b-it chat template, greedy-decoded for 256 tokens, and labelled by the Qwen/Qwen3-8B judge. The gap between base_plus_attn and the adapter arms isolates what the trained sparse transcoder contributes to refusal with attention held fixed (+57 pp on harmful prompts).

Files

Two folders, one per run (the "experiment-name"):

folder / experiment-name	Slurm job	contents
`refusal_ladder/`	16717433	`harm_<id>.md` (63) + `benign_<id>.md` (30); each file holds the request and, per arm, the judge label/confidence/rationale and the full response for all six arms below
`refusal_ladder_hybrid_ftonly/`	16717626	same 93 prompts, only the corrected `hybrid_ft` arm (GemmaScope replacement restricted to the fine-tuned layers 0/24/25); its labels were grafted into the main `results.json`

arm	model	description
`base`	`google/gemma-2-2b`	un-tuned base model
`base_plus_attn`	adapter checkpoint with its transcoder decoder zeroed	instruct attention/embeddings/LayerNorm + base MLPs, no transcoder
`hybrid_ft`	base model with GemmaScope transcoders (instruct-fine-tuned at layers 0/24/25, `siddharthmb/2026.TA.gemma2_2b_gemmascope_transcoders_instruct_ft_L0-24-25`) replacing those MLPs	can the fine-tuned base transcoders alone carry the forward pass
`adapter_tc8192`	`siddharthmb/2026.TA.gemma2_2b_tc8192_decb_l1w0.001_tarbb_lb2.0_ln1_dr20000_lr8e-04_bs4_sl14793860`	deployed sparse transcoder adapter
`adapter_huge`	`siddharthmb/2026.TA.gemma2_2b_huge_tc16384_decb_l1w0.0003_norm_sch_tarbb_lb2.0_ln1.0_dr500000_lr2e-04_bs8_sl`	16384-feature adapter
`instruct`	`google/gemma-2-2b-it`	instruction-tuned target

Regenerate

GPU node (jagupard), repo root, LARGE_ARTIFACTS_DIR + HF_TOKEN exported:

uv run --no-sync python experiments/refusal_tracing/scripts/eval_refusal_ladder.py --max_new_tokens 256 --batch_size 8 --judge_batch_size 8 --output_dir experiments/refusal_tracing/results/refusal_ladder
uv run --no-sync python experiments/refusal_tracing/scripts/eval_refusal_ladder.py --arms hybrid_ft --hybrid_replace_layers finetuned --max_new_tokens 256 --output_dir experiments/refusal_tracing/results/refusal_ladder_hybrid_ftonly
uv run --no-sync python experiments/refusal_tracing/scripts/eval_refusal_ladder.py --report_only --output_dir experiments/refusal_tracing/results/refusal_ladder   # re-render tables + chart, no GPU

Cluster paths

Slurm logs: logs/interesting_queries/20260810_142433_16717433.{out,err}, logs/interesting_queries/20260810_144334_16717626.{out,err} (checkout /juice2/u/siddharth/transcoder-adapters).
In git: experiments/refusal_tracing/results/refusal_ladder{,_hybrid_ftonly}/{results.json,summary.md,per_prompt_labels.md,refusal_ladder.png}.

Restore into the repo

uv run hf download siddharthmb/2026.TA.experiments.refusal_tracing.refusal_ladder --repo-type dataset --include "refusal_ladder/*" --local-dir /tmp/rl && mv /tmp/rl/refusal_ladder experiments/refusal_tracing/results/refusal_ladder/transcripts
uv run hf download siddharthmb/2026.TA.experiments.refusal_tracing.refusal_ladder --repo-type dataset --include "refusal_ladder_hybrid_ftonly/*" --local-dir /tmp/rl && mv /tmp/rl/refusal_ladder_hybrid_ftonly experiments/refusal_tracing/results/refusal_ladder_hybrid_ftonly/transcripts

Provenance

Code: experiments/refusal_tracing/scripts/ in the transcoder-adapters repo; writeup: experiments/refusal_tracing/writeup.md.
Aggregates (results.json with every record incl. judge label, confidence and rationale; summary.md tables; figures) stay in git next to the transcripts.txt breadcrumb that points here. The transcript .md files are a human-readable rendering of results.json records.
Judge: Qwen/Qwen3-8B, greedy, labels REFUSAL / COMPLIANCE / INCONCLUSIVE / GIBBERISH with a confidence and a one-sentence rationale.
Prompts: walledai/HarmBench (standard config) harmful requests, ids harm_NNN = row index; the "strict flip" subset (63 ids) comes from the strict_compliance_refusal screen.
No Weights & Biases runs (generation + judging only).

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