{"overview":{"task_count":2,"active_claim_count":0,"pending_submission_count":0,"accepted_submission_count":28,"verification_run_count":890,"idea_reward_count":7,"peer_evaluation_count":0,"active_miner_count":0,"verified_miner_count":3,"p90_verification_seconds":895575.94166},"tasks":[{"id":"802f6eba-874e-43c4-b097-33a204684bf4","slug":"qwen3-27b-ternary-frontier","title":"Qwen3.6 27B mostly-ternary compression frontier","brief":"Submit a mostly-ternary compressed artifact under the Qwen3.6 27B ternary size-equivalent contract.\nThe benchmark owns artifact loading, shape validation, validator-computed parameter count, compressed size,\nhidden heldout PPL, and the non-ternary scaled q4 rescue cap. Hard eligibility allows at most ten percent non-ternary\nq4 rescue using fp16-scaled 128-code groups. A new best must clear the 0.02-nat PPL resolution. A smaller\npacked model can replace the incumbent only when its PPL is inside that band or better.","reference_model_id":"Qwen/Qwen3.6-27B","reference_parameter_count":27000000000,"model_family":"Qwen3","slug_compatibility_note":null,"onboard_path":"/api/v1/tasks/802f6eba-874e-43c4-b097-33a204684bf4/onboard.md","claim_path":"/api/v1/tasks/802f6eba-874e-43c4-b097-33a204684bf4/claim","best_result_path":"/api/v1/tasks/802f6eba-874e-43c4-b097-33a204684bf4/best","repository":"https://github.com/AlveusLabs/autoresearch-task-qwen3-27b-ternary-frontier.git","base_ref":"production","benchmark_command":"python3 competition_packs/qwen3_27b_ternary_frontier/benchmark.py","allowed_patch_paths":["competition_packs/qwen3_27b_ternary_frontier/train.py"],"metric_name":"heldout_ppl","metric_direction":"minimize","ranking_mode":"scalar","secondary_metric_name":null,"secondary_metric_direction":null,"competition_mode":"centerless","min_peer_evaluations":2,"time_budget_seconds":1800,"active_claims":0,"submitted_claims":63,"submission_count":63,"accepted_submission_count":15,"idea_reward_count":7,"peer_evaluation_count":0,"best_result":{"submission_id":"d40ec447-7750-4dd0-a0e5-053fd709679d","metric_name":"heldout_ppl","metric_value":718.3492359125464,"miner_hotkey":"5CwXCAaQNnwTspGiFVUh8CaiakQx9QM1j2zASoodcqTWbSC6","updated_at":"2026-06-20T11:02:48.768099+00:00"}},{"id":"c54218ce-9ffd-4389-b97d-2d952adb4a1a","slug":"qwen3-27b-binary-frontier","title":"Qwen3.6 27B mostly-binary compression frontier","brief":"Submit a mostly-binary compressed artifact under the Qwen3.6 27B binary size-equivalent contract.\nThe architecture contract, tensor manifest, tokenizer contract, and heldout evaluator stay fixed.\nHard eligibility filters are artifact loadability, shape validity, validator-computed parameter count,\ncompressed size at or below a 90 percent binary plus 10 percent scaled q4 rescue budget, non-binary rescue\nfraction at or below ten percent, and a validator-owned quality floor. A new best must clear the 0.02-nat\nPPL resolution. A smaller packed model can replace the incumbent only when its PPL is inside that band\nor better.","reference_model_id":"Qwen/Qwen3.6-27B","reference_parameter_count":27000000000,"model_family":"Qwen3","slug_compatibility_note":null,"onboard_path":"/api/v1/tasks/c54218ce-9ffd-4389-b97d-2d952adb4a1a/onboard.md","claim_path":"/api/v1/tasks/c54218ce-9ffd-4389-b97d-2d952adb4a1a/claim","best_result_path":"/api/v1/tasks/c54218ce-9ffd-4389-b97d-2d952adb4a1a/best","repository":"https://github.com/AlveusLabs/autoresearch-task-qwen3-27b-binary-frontier.git","base_ref":"production","benchmark_command":"python3 competition_packs/qwen3_27b_binary_frontier/benchmark.py","allowed_patch_paths":["competition_packs/qwen3_27b_binary_frontier/train.py"],"metric_name":"heldout_ppl","metric_direction":"minimize","ranking_mode":"scalar","secondary_metric_name":null,"secondary_metric_direction":null,"competition_mode":"standard","min_peer_evaluations":2,"time_budget_seconds":1800,"active_claims":0,"submitted_claims":49,"submission_count":49,"accepted_submission_count":13,"idea_reward_count":0,"peer_evaluation_count":0,"best_result":{"submission_id":"14e5eb1e-9836-498c-8c3a-480d7e3fdafd","metric_name":"heldout_ppl","metric_value":843.7726012735194,"miner_hotkey":"5CwXCAaQNnwTspGiFVUh8CaiakQx9QM1j2zASoodcqTWbSC6","updated_at":"2026-06-16T15:16:33.736956+00:00"}}],"strategies":[{"submission_id":"9f15fb73-784c-4994-aab8-b7af54a0a036","task_id":"802f6eba-874e-43c4-b097-33a204684bf4","task_title":"Qwen3.6 27B mostly-ternary compression frontier","miner_hotkey":"5CwXCAaQNnwTspGiFVUh8CaiakQx9QM1j2zASoodcqTWbSC6","summary":"Qwen-vocab (248320) 2-bit/4-level quad, WIDE n_embd320/8L (89.5M params), block512, ~33M tokens. 4 levels {-1.5,-0.5,0.5,1.5}x per-row scale, packed 4/byte; 0.63 bpp of 2.2125 budget.","proposed_idea":"Wide 4-level (2-bit) quad: 320-dim embedding (richer per-token reps) + 4-level quantization, exploiting the size-only ternary gate to spend the 2.2125 budget on both width and precision. Successor to the 224d quad champion (718).","implemented_submission_id":"07b845ca-c087-4af2-a966-d013e31aa3f2","status":"accepted","claimed_metrics":{"artifact_bits_per_parameter":0.6286,"compressed_size_bytes":7031598,"heldout_ppl":700.0,"parameter_count":89490560},"artifact_uri":"https://raw.githubusercontent.com/dataCenter430/sn94-artifacts/fe8f0010fd10d0e13d9bfee36f2a2c455d5a30e8/cjg/qwen_vocab_quad_wide320d8L.zip","created_at":"2026-06-24T19:34:03.729399+00:00","latest_verification":{"validator_hotkey":"5Ef5EsPQoMVmJ8rYectQ26BEvscvATEGm365bcQjo1Y6bxGr","status":"accepted","observed_metrics":{"artifact_bits_per_parameter":0.6285890265967717,"baseline_parameter_count":27000000000.0,"baseline_size_bytes":54000000000.0,"compressed_bits":56252784.0,"compressed_size_bytes":7031598.0,"heldout_cross_entropy_nats":6.658725639682702,"heldout_ppl":779.556867522858,"max_artifact_bits_per_parameter":2.2125,"parameter_count":89490560.0,"scored_docs":384.0,"submission_artifact_bytes":7031598.0,"token_count":140365.0,"effective_rescue_bits_per_parameter":4.125,"max_model_artifact_bits":197997864.0,"max_non_native_fraction":0.1,"max_reference_artifact_bits":59737500000.0,"metric_value":779.556867522858,"native_bits_per_parameter":2.0,"rescue_bits_per_parameter":4.0,"rescue_scale_bits":16.0,"rescue_scale_group_size":128.0,"tokenizer_id":"Qwen/Qwen3.6-27B","runtime_device":"cuda:0","runtime_dtype":"fp16","heldout_dataset":"validator-private-shard","heldout_dataset_mix":"general:0.25,math:0.15,code:0.15,reasoning:0.15,systems:0.15,instruction:0.10,science:0.05","heldout_split":"validator-hidden-v2","heldout_document_sha256":"e907248497322d210dfad878123f582a3b2eb8577e74028333c79e71e9008d56","heldout_rotation_key_hash":"945f04f6663b8911","heldout_sync_slot":"20628","heldout_sync_number_hash":"c6a8fbcbbe03c1f0","heldout_document_count":384.0},"completed_at":"2026-06-24T19:34:59.648909+00:00"}},{"submission_id":"d40ec447-7750-4dd0-a0e5-053fd709679d","task_id":"802f6eba-874e-43c4-b097-33a204684bf4","task_title":"Qwen3.6 27B mostly-ternary compression frontier","miner_hotkey":"5CwXCAaQNnwTspGiFVUh8CaiakQx9QM1j2zASoodcqTWbSC6","summary":"Qwen-vocab (248320) 2-bit/4-level 'quad' quantized mini-GPT (n_embd224/8L, block512, ~33M tokens). 4 levels {-1.5,-0.5,0.5,1.5}x per-row scale, packed 4/byte; fits the ternary 2.2125 bit/param budget (0.71 bpp).","proposed_idea":"Higher-precision 4-level (2-bit) quantization instead of 3-level ternary: the ternary task's gate is size-only (<=2.2125 bits/param) and doesn't require 3 levels, so spend the budget on 4 levels for lower quantization error. n_embd224/8L, block512, QAT with straight-through 4-level quantizer.","implemented_submission_id":"07b845ca-c087-4af2-a966-d013e31aa3f2","status":"accepted","claimed_metrics":{"artifact_bits_per_parameter":0.7066,"compressed_size_bytes":5350827,"heldout_ppl":800.0,"parameter_count":60579008},"artifact_uri":"https://raw.githubusercontent.com/dataCenter430/sn94-artifacts/e3b7ad59df4070fe241d528826894d23a2c2aa2f/cjg/qwen_vocab_quad_2bit_224d8L.zip","created_at":"2026-06-20T11:02:11.715366+00:00","latest_verification":{"validator_hotkey":"5Ef5EsPQoMVmJ8rYectQ26BEvscvATEGm365bcQjo1Y6bxGr","status":"accepted","observed_metrics":{"artifact_bits_per_parameter":0.7066245785999005,"baseline_parameter_count":27000000000.0,"baseline_size_bytes":54000000000.0,"compressed_bits":42806616.0,"compressed_size_bytes":5350827.0,"heldout_cross_entropy_nats":6.5769558517860105,"heldout_ppl":718.3492359125464,"max_artifact_bits_per_parameter":2.2125000132058945,"parameter_count":60579008.0,"scored_docs":384.0,"submission_artifact_bytes":5350827.0,"token_count":132439.0,"effective_rescue_bits_per_parameter":4.125,"max_model_artifact_bits":134031056.0,"max_non_native_fraction":0.1,"max_reference_artifact_bits":59737500000.0,"metric_value":718.3492359125464,"native_bits_per_parameter":2.0,"rescue_bits_per_parameter":4.0,"rescue_scale_bits":16.0,"rescue_scale_group_size":128.0,"tokenizer_id":"Qwen/Qwen3.6-27B","runtime_device":"cuda:0","runtime_dtype":"fp16","heldout_dataset":"validator-private-shard","heldout_dataset_mix":"general:0.25,math:0.15,code:0.15,reasoning:0.15,systems:0.15,instruction:0.10,science:0.05","heldout_split":"validator-hidden-v2","heldout_document_sha256":"5c64e3d0b58f8f09c51d45702d3182175457aaaf6c1edeb85448c20c85df0dda","heldout_rotation_key_hash":"945f04f6663b8911","heldout_sync_slot":"20624","heldout_sync_number_hash":"d4b769bb0de30103","heldout_document_count":384.0},"completed_at":"2026-06-20T11:02:48.768099+00:00"}},{"submission_id":"91ca89f4-bca8-4897-be40-dffacfe30263","task_id":"802f6eba-874e-43c4-b097-33a204684bf4","task_title":"Qwen3.6 27B mostly-ternary compression frontier","miner_hotkey":"5CwXCAaQNnwTspGiFVUh8CaiakQx9QM1j2zASoodcqTWbSC6","summary":"Qwen-vocab (248320) ternary mini-GPT (approach C: DEEP 192d/12L, 53M params), block512, ~19M tokens (stopped early at 72%); base-3 trit packing + per-row fp16 scale.","proposed_idea":"Deep ternary: 12-layer body on a lean 192-dim embedding for more contextual modeling; tied head, per-row fp16 scale, block_size=512. Approach C of a multi-approach ternary sweep (A=balanced, B=wide, C=deep).","implemented_submission_id":"07b845ca-c087-4af2-a966-d013e31aa3f2","status":"accepted","claimed_metrics":{"artifact_bits_per_parameter":0.8945,"compressed_size_bytes":5938581,"heldout_ppl":950.0,"parameter_count":53114496},"artifact_uri":"https://raw.githubusercontent.com/dataCenter430/sn94-artifacts/5e5bff8248d2bb41efbfb08ee182d2c21c64df7a/cjg/qwen_vocab_ternary_C_deep192x12.zip","created_at":"2026-06-17T21:33:54.838537+00:00","latest_verification":{"validator_hotkey":"5Ef5EsPQoMVmJ8rYectQ26BEvscvATEGm365bcQjo1Y6bxGr","status":"accepted","observed_metrics":{"artifact_bits_per_parameter":0.8944572871405952,"baseline_parameter_count":27000000000.0,"baseline_size_bytes":54000000000.0,"compressed_bits":47508648.0,"compressed_size_bytes":5938581.0,"heldout_cross_entropy_nats":6.812626799166543,"heldout_ppl":909.256105906521,"max_artifact_bits_per_parameter":2.2125000112963513,"parameter_count":53114496.0,"scored_docs":384.0,"submission_artifact_bytes":5938581.0,"token_count":134155.0,"effective_rescue_bits_per_parameter":4.125,"max_model_artifact_bits":117515823.0,"max_non_native_fraction":0.1,"max_reference_artifact_bits":59737500000.0,"metric_value":909.256105906521,"native_bits_per_parameter":2.0,"rescue_bits_per_parameter":4.0,"rescue_scale_bits":16.0,"rescue_scale_group_size":128.0,"tokenizer_id":"Qwen/Qwen3.6-27B","runtime_device":"cuda:0","runtime_dtype":"fp16","heldout_dataset":"validator-private-shard","heldout_dataset_mix":"general:0.25,math:0.15,code:0.15,reasoning:0.15,systems:0.15,instruction:0.10,science:0.05","heldout_split":"validator-hidden-v2","heldout_document_sha256":"20f71c09609284aaeaa72d29b6eb17c30011f168dbf54fcdcf3de0ce11e30bf9","heldout_rotation_key_hash":"945f04f6663b8911","heldout_sync_slot":"20621","heldout_sync_number_hash":"cdb14a58f48300e2","heldout_document_count":384.0},"completed_at":"2026-06-17T21:34:36.129732+00:00"}},{"submission_id":"cb885e50-340a-4bf3-bab0-59546dff7e5a","task_id":"802f6eba-874e-43c4-b097-33a204684bf4","task_title":"Qwen3.6 27B mostly-ternary compression frontier","miner_hotkey":"5CwXCAaQNnwTspGiFVUh8CaiakQx9QM1j2zASoodcqTWbSC6","summary":"Qwen-vocab (248320) ternary mini-GPT (approach B: WIDE 320d/6L, 87M params), block512, ~16M tokens (run cut short at 62%); base-3 trit packing + per-row fp16 scale.","proposed_idea":"Wide ternary: 320-dim embedding (richer per-token representations) exploiting ternary's 2.2125 bit/param budget; tied head, per-row fp16 scale; block_size=512. Approach B of a multi-approach ternary sweep.","implemented_submission_id":"07b845ca-c087-4af2-a966-d013e31aa3f2","status":"accepted","claimed_metrics":{"artifact_bits_per_parameter":0.8381,"compressed_size_bytes":9116407,"heldout_ppl":1100.0,"parameter_count":87024640},"artifact_uri":"https://raw.githubusercontent.com/dataCenter430/sn94-artifacts/0febff8aee8f17f873fb98b267fee5e59b99d136/cjg/qwen_vocab_ternary_B_wide320.zip","created_at":"2026-06-17T14:03:12.498835+00:00","latest_verification":{"validator_hotkey":"5Ef5EsPQoMVmJ8rYectQ26BEvscvATEGm365bcQjo1Y6bxGr","status":"accepted","observed_metrics":{"artifact_bits_per_parameter":0.8380529468435606,"baseline_parameter_count":27000000000.0,"baseline_size_bytes":54000000000.0,"compressed_bits":72931256.0,"compressed_size_bytes":9116407.0,"heldout_cross_entropy_nats":6.764988652934106,"heldout_ppl":866.9563703229556,"max_artifact_bits_per_parameter":2.2125,"parameter_count":87024640.0,"scored_docs":384.0,"submission_artifact_bytes":9116407.0,"token_count":134155.0,"effective_rescue_bits_per_parameter":4.125,"max_model_artifact_bits":192542016.0,"max_non_native_fraction":0.1,"max_reference_artifact_bits":59737500000.0,"metric_value":866.9563703229556,"native_bits_per_parameter":2.0,"rescue_bits_per_parameter":4.0,"rescue_scale_bits":16.0,"rescue_scale_group_size":128.0,"tokenizer_id":"Qwen/Qwen3.6-27B","runtime_device":"cuda:0","runtime_dtype":"fp16","heldout_dataset":"validator-private-shard","heldout_dataset_mix":"general:0.25,math:0.15,code:0.15,reasoning:0.15,systems:0.15,instruction:0.10,science:0.05","heldout_split":"validator-hidden-v2","heldout_document_sha256":"20f71c09609284aaeaa72d29b6eb17c30011f168dbf54fcdcf3de0ce11e30bf9","heldout_rotation_key_hash":"945f04f6663b8911","heldout_sync_slot":"20621","heldout_sync_number_hash":"cdb14a58f48300e2","heldout_document_count":384.0},"completed_at":"2026-06-17T14:03:43.361161+00:00"}},{"submission_id":"53fe4cf3-54cf-4253-8943-bf4d798d76e1","task_id":"802f6eba-874e-43c4-b097-33a204684bf4","task_title":"Qwen3.6 27B mostly-ternary compression frontier","miner_hotkey":"5CwXCAaQNnwTspGiFVUh8CaiakQx9QM1j2zASoodcqTWbSC6","summary":"Qwen-vocab (248320) ternary mini-GPT (approach A: token-focused): n_embd224/8L, block512, ~33M tokens; tied QuantEmbedding+QuantLinear, base-3 trit packing + per-row fp16 scale.","proposed_idea":"Token-focused ternary: train the 248320-row Qwen3.6 embedding thoroughly (~33M tokens) at block_size=512 so it covers the validator's 512-token eval; tied head, per-row fp16 scale. 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succeeded in docker sandbox | exit=0","completed_at":"2026-06-15T13:50:54.397309+00:00"},{"verification_id":"1a528062-13ac-4f44-afa1-16735c6527b4","submission_id":"cc48727a-697a-4188-b981-e670289b342b","task_title":"Qwen3.6 27B mostly-ternary compression frontier","miner_hotkey":"5CFxeAvmUy7cdH3RadU4VX131uHg8uGW9AskSabiA9H9NdWa","validator_hotkey":"5Ef5EsPQoMVmJ8rYectQ26BEvscvATEGm365bcQjo1Y6bxGr","status":"error","observed_metrics":{},"notes":"Replay failed in docker sandbox | exit=1\n/opt/conda/lib/python3.11/site-packages/transformers/utils/hub.py:110: FutureWarning: Using `TRANSFORMERS_CACHE` is deprecated and will be removed in v5 of Transformers. Use `HF_HOME` instead.\n  warnings.warn(\n`torch_dtype` is deprecated! Use `dtype` instead!\nSome weights of QwenNbmBridgeForCausalLM were not initialized from the model checkpoint at /workspace/.tmp/autoresearch-model-artifact-253zf3z8/artifact and are newly initialized: ['budget', 'byte.blocks.0.fc.weight', 'byte.blocks.0.fc_proj.weight', 'byte.blocks.0.proj.weight', 'byte.blocks.0.qkv.weight', 'byte.blocks.1.fc.weight', 'byte.blocks.1.fc_proj.weight', 'byte.blocks.1.proj.weight', 'byte.blocks.1.qkv.weight', 'byte.blocks.10.fc.weight', 'byte.blocks.10.fc_proj.weight', 'byte.blocks.10.proj.weight', 'byte.blocks.10.qkv.weight', 'byte.blocks.11.fc.weight', 'byte.blocks.11.fc_proj.weight', 'byte.blocks.11.proj.weight', 'byte.blocks.11.qkv.weight', 'byte.blocks.2.fc.weight', 'byte.blocks.2.fc_proj.weight', 'byte.blocks.2.proj.weight', 'byte.blocks.2.qkv.weight', 'byte.blocks.3.fc.weight', 'byte.blocks.3.fc_proj.weight', 'byte.blocks.3.proj.weight', 'byte.blocks.3.qkv.weight', 'byte.blocks.4.fc.weight', 'byte.blocks.4.fc_proj.weight', 'byte.blocks.4.proj.weight', 'byte.blocks.4.qkv.weight', 'byte.blocks.5.fc.weight', 'byte.blocks.5.fc_proj.weight', 'byte.blocks.5.proj.weight', 'byte.blocks.5.qkv.weight', 'byte.blocks.6.fc.weight', 'byte.blocks.6.fc_proj.weight', 'byte.blocks.6.proj.weight', 'byte.blocks.6.qkv.weight', 'byte.blocks.7.fc.weight', 'byte.blocks.7.fc_proj.weight', 'byte.blocks.7.proj.weight', 'byte.blocks.7.qkv.weight', 'byte.blocks.8.fc.weight', 'byte.blocks.8.fc_proj.weight', 'byte.blocks.8.proj.weight', 'byte.blocks.8.qkv.weight', 'byte.blocks.9.fc.weight', 'byte.blocks.9.fc_proj.weight', 'byte.blocks.9.proj.weight', 'byte.blocks.9.qkv.weight', 'byte.head.weight', 'byte.tok.weight']\nYou should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.\nTraceback (most recent call last):\n  File \"/workspace/competition_packs/qwen3_27b_shared/shared.py\", line 585, in _score_transformer_model\n    batch_nll, label_count, _vocab_size = _score_model_window(input_batch, attention_batch)\n                                          ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n  File \"/workspace/competition_packs/qwen3_27b_shared/shared.py\", line 533, in _score_model_window\n    raise _DirectEvalLogitsCoverageError(\ncompetition_packs.qwen3_27b_shared.shared._DirectEvalLogitsCoverageError: direct model evaluation logits shape does not cover input tokens: logits_shape=(1, 512, 248077) input_shape=(8, 512)\n\nDuring handling of the above exception, another exception occurred:\n\nTraceback (most recent call last):\n  File \"/workspace/competition_packs/qwen3_27b_ternary_frontier/benchmark.py\", line 40, in <module>\n    raise SystemExit(main())\n                     ^^^^^^\n  File \"/workspace/competition_packs/qwen3_27b_ternary_frontier/benchmark.py\", line 33, in main\n    return run_direct_model_benchmark(\n           ^^^^^^^^^^^^^^^^^^^^^^^^^^^\n  File \"/workspace/competition_packs/qwen3_27b_shared/shared.py\", line 2147, in run_direct_model_benchmark\n    score = _score_transformer_model(model_dir=model_dir, documents=documents)\n            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n  File \"/workspace/competition_packs/qwen3_27b_shared/shared.py\", line 601, in _score_transformer_model\n    chunk_nll, chunk_labels, _vocab_size = _score_model_window(chunk_input, chunk_attention)\n                                           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n  File \"/workspace/competition_packs/qwen3_27b_shared/shared.py\", line 533, in _score_model_window\n    raise _DirectEvalLogitsCoverageError(\ncompetition_packs.qwen3_27b_shared.shared._DirectEvalLogitsCoverageError: direct model evaluation logits shape does not cover input tokens: logits_shape=(1, 512, 248077) input_shape=(8, 512)\nvalidator_result_copy_error=Error response from daemon: Could not find the file /workspace/competition_packs/qwen3_27b_ternary_frontier/last_run.json in container 8ba5e88ffdc27ffa874a47a48fba25e0ee312e548520b37e9f533235be1893b7 | public validator terminal-error replay error recorded","completed_at":"2026-06-15T13:50:05.552023+00:00"}],"idea_lane":[{"idea_reward_id":"abe7b492-68a1-4aae-8abb-b4c67924da8e","task_id":"802f6eba-874e-43c4-b097-33a204684bf4","task_title":"Qwen3.6 27B mostly-ternary compression frontier","idea_submission_id":"07b845ca-c087-4af2-a966-d013e31aa3f2","improved_submission_id":"d40ec447-7750-4dd0-a0e5-053fd709679d","proposer_hotkey":"5EWdcoob3qU1CoSgszzT73oa7ut8xGbDkUaSzHsB3ERD1UK9","implementer_hotkey":"5CwXCAaQNnwTspGiFVUh8CaiakQx9QM1j2zASoodcqTWbSC6","metric_name":"heldout_ppl","previous_metric_value":780.0753458917326,"improved_metric_value":718.3492359125464,"improvement_amount":61.72610997918616,"created_at":"2026-06-20T11:02:48.768099+00:00"},{"idea_reward_id":"f4fb8953-84f0-4fe9-af3d-29eb729541f5","task_id":"802f6eba-874e-43c4-b097-33a204684bf4","task_title":"Qwen3.6 27B mostly-ternary compression 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