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onboarding-countdown-qwen3-1.7b
run_countdown.py
Qwen/Qwen3-1.7B
{"temperature": 0.7, "max_tokens": 4096, "top_p": 0.9}
[]
Tutorial experiment: Qwen3-1.7B on 8 Countdown problems (3-4 operands, targets 10-99)
["onboarding", "countdown", "tutorial", "qwen3-1.7b"]
{"experiment_name": "onboarding", "job_id": "vista:662880", "cluster": "vista", "artifact_status": "final", "canary": true}
2026-04-12T23:39:40.773794+00:00
null
null
null
null
null
null
-1
2026-04-12T23:39:40.773794+00:00
llmrecourse-calibrated-retrieval-test-2samples-v1
multihop_dinco_minicheck_hotpotqa.py
Qwen/Qwen3-8B + Bespoke-MiniCheck-7B
{"nvc_threshold": 0.7, "grounding_threshold": 0.7, "combined_threshold": 0.65, "prior_weight": 0.6, "policy_mode": "threshold", "qwen_dtype": "bfloat16", "minicheck_gpu_memory_utilization": 0.45, "seed": 17, "max_examples": 2, "start_idx": 0}
["hotpotqa/hotpot_qa (distractor, validation)"]
2-sample smoke test of DINCO+MiniCheck multi-hop retrieval controller on HotpotQA distractor validation
["llmrecourse-calibrated-retrieval", "canary", "hotpotqa", "dinco", "minicheck"]
{"experiment_name": "llmrecourse-calibrated-retrieval", "job_id": "vista:663034", "cluster": "vista", "artifact_status": "final", "canary": true}
2026-04-13T01:47:02.597387+00:00
null
null
null
null
null
null
-1
2026-04-13T01:47:02.597387+00:00
llmrecourse-calibrated-retrieval-agent-gated-canary-v1
run_agent_gated_retrieval_hotpotqa.py
Qwen/Qwen3-32B
{"agent_max_turns": 6, "agent_max_new_tokens": 512, "model_name": "Qwen/Qwen3-32B", "minicheck_model": "Bespoke-MiniCheck-7B", "minicheck_max_model_len": 4096, "seed": 42, "shuffle": true, "limit": 5, "indexed_pool_limit": 2000}
["hotpotqa/hotpot_qa (distractor, validation)"]
Agent-gated calibrated retrieval canary: 5 HotpotQA examples with Qwen3-32B + MiniCheck-7B. Agent receives DINCO confidence and MiniCheck grounding telemetry to decide actions (commit/retrieve/refine/decompose). EM=0.40, F1=0.61. Zero parse failures, agent uses telemetry in all decisions.
["llmrecourse-calibrated-retrieval", "agent-gated", "canary", "hotpotqa"]
{"experiment_name": "llmrecourse-calibrated-retrieval", "job_id": "vista:663159", "cluster": "vista", "artifact_status": "final", "canary": true}
2026-04-13T04:09:09.005566+00:00
null
null
null
null
null
null
-1
2026-04-13T04:09:09.005566+00:00
llmrecourse-calibrated-retrieval-agent-gated-50-v1
run_agent_gated_retrieval_hotpotqa.py
Qwen/Qwen3-32B
{"agent_max_turns": 6, "agent_max_new_tokens": 512, "seed": 42, "indexed_pool_limit": 2000, "minicheck_max_model_len": 4096}
[]
Agent-gated calibrated retrieval on HotpotQA — FINAL (50/50 examples). Agent receives DINCO+MiniCheck telemetry, decides commit/retrieve/refine/decompose. EM=0.560, F1=0.737.
["llmrecourse-calibrated-retrieval", "agent-gated", "hotpotqa", "final"]
{"experiment_name": "llmrecourse-calibrated-retrieval", "job_id": "vista:663208", "cluster": "vista", "artifact_status": "final", "canary": false}
2026-04-13T07:44:23.454634+00:00
null
null
null
null
null
null
-1
2026-04-13T05:59:17.651670+00:00
llmrecourse-calibrated-retrieval-origbeam-50-v1
run_calibrated_retrieval_hotpotqa_qwen32b_origbeam.py
Qwen/Qwen3-32B
{"dinco_threshold": 0.8, "minicheck_g_mean_threshold": 0.7, "minicheck_g_min_threshold": 0.5, "seed": 42, "indexed_pool_limit": 2000, "minicheck_max_model_len": 4096}
[]
Origbeam threshold-based calibrated retrieval on HotpotQA — FINAL (50/50 examples). Hardcoded thresholds: DINCO>=0.80 skip retrieval, g_mean>=0.70 accept grounded. EM=0.480, F1=0.672.
["llmrecourse-calibrated-retrieval", "origbeam", "hotpotqa", "final"]
{"experiment_name": "llmrecourse-calibrated-retrieval", "job_id": "vista:663209", "cluster": "vista", "artifact_status": "final", "canary": false}
2026-04-13T07:44:55.945852+00:00
null
null
null
null
null
null
-1
2026-04-13T05:59:26.690167+00:00
llmrecourse-calibrated-retrieval-fullcontext-50-v1
hotpotqa_qwen32b_fullcontext_baseline.py
Qwen/Qwen3-32B
{"max_new_tokens": 256, "max_model_len": 8192, "enable_thinking": false, "seed": 42, "indexed_pool_limit": 2000}
[]
Full-context baseline on HotpotQA — FINAL (50/50 examples). All 10 distractor paragraphs given to model. vLLM with enable_thinking=False. EM=0.480, F1=0.704. Ceiling baseline for retrieval comparison.
["llmrecourse-calibrated-retrieval", "full-context", "hotpotqa", "baseline", "final"]
{"experiment_name": "llmrecourse-calibrated-retrieval", "job_id": "vista:663443", "cluster": "vista", "artifact_status": "final", "canary": false}
2026-04-13T07:45:20.023607+00:00
null
null
null
null
null
null
-1
2026-04-13T07:45:20.023607+00:00
llmrecourse-calibrated-retrieval-ab50-stateless-v1
calibandretrieve/run_agent_gated_retrieval_hotpotqa.py
Qwen/Qwen3-32B
{"agent_prompt_mode": "stateless", "agent_max_turns": 6, "agent_max_new_tokens": 512, "seed": 42, "limit": 50, "indexed_pool_limit": 2000, "gate_threshold": 0.8, "retrieval_top_k": 8, "generator_dtype": "bfloat16"}
[]
Agent-gated calibrated retrieval on HotpotQA — 50-example STATELESS baseline (seed 42). Part of stateless vs multi-turn A/B comparison.
["llmrecourse-calibrated-retrieval", "ab-test", "stateless", "hotpotqa", "qwen3-32b"]
{"experiment_name": "llmrecourse-calibrated-retrieval", "job_id": "vista:664398", "cluster": "vista", "artifact_status": "final", "canary": false, "results_summary": {"mean_em": 0.58, "mean_f1": 0.7565, "avg_nodes": 1.86, "retrieved_nodes": 0, "agent_turns_total": 188}}
2026-04-14T16:34:07.965007+00:00
null
null
null
null
null
null
-1
2026-04-14T16:34:07.965007+00:00
llmrecourse-calibrated-retrieval-ab50-multiturn-v1
calibandretrieve/run_agent_gated_retrieval_hotpotqa.py
Qwen/Qwen3-32B
{"agent_prompt_mode": "multi_turn", "agent_max_turns": 6, "agent_max_new_tokens": 512, "agent_max_context_tokens": 16384, "seed": 42, "limit": 50, "indexed_pool_limit": 2000, "gate_threshold": 0.8, "retrieval_top_k": 8, "generator_dtype": "bfloat16"}
[]
Agent-gated calibrated retrieval on HotpotQA — 50-example MULTI-TURN arm (seed 42). Part of stateless vs multi-turn A/B comparison. EM=0.560, F1=0.737.
["llmrecourse-calibrated-retrieval", "ab-test", "multi-turn", "hotpotqa", "qwen3-32b"]
{"experiment_name": "llmrecourse-calibrated-retrieval", "job_id": "vista:664399", "cluster": "vista", "artifact_status": "final", "canary": false, "results_summary": {"mean_em": 0.56, "mean_f1": 0.7365, "avg_nodes": 1.86, "agent_turns_total": 187, "ab_comparison": "Identical to stateless on 49/50 questions. Single flip...
2026-04-14T17:11:05.306953+00:00
null
null
null
null
null
null
-1
2026-04-14T17:11:05.306953+00:00
llmrecourse-calibrated-retrieval-ab50-notelemetry-stateless-v1
run_agent_gated_retrieval_hotpotqa.py
Qwen/Qwen3-32B
{"agent_prompt_mode": "stateless", "agent_telemetry_mode": "no_telemetry", "agent_max_turns": 6, "seed": 42}
[]
Stateless agent-gated retrieval WITHOUT telemetry (ablation). No DINCO/MiniCheck shown to agent. EM=0.560, F1=0.741. 139 retrieves, 2.7 avg turns/sq.
["llmrecourse-calibrated-retrieval", "ablation", "no-telemetry"]
{"experiment_name": "llmrecourse-calibrated-retrieval", "job_id": "vista:666636", "cluster": "vista", "artifact_status": "final", "canary": false}
2026-04-15T20:40:51.304453+00:00
null
null
null
null
null
null
-1
2026-04-15T20:40:51.304453+00:00
llmrecourse-calibrated-retrieval-ab50-notelemetry-multiturn-v1
run_agent_gated_retrieval_hotpotqa.py
Qwen/Qwen3-32B
{"agent_prompt_mode": "multi_turn", "agent_telemetry_mode": "no_telemetry", "agent_max_turns": 6, "seed": 42}
[]
Multi-turn agent-gated retrieval WITHOUT telemetry (ablation). No DINCO/MiniCheck shown to agent. EM=0.540, F1=0.718. 94 retrieves, 2.0 avg turns/sq.
["llmrecourse-calibrated-retrieval", "ablation", "no-telemetry"]
{"experiment_name": "llmrecourse-calibrated-retrieval", "job_id": "vista:666637", "cluster": "vista", "artifact_status": "final", "canary": false}
2026-04-15T20:41:56.129079+00:00
null
null
null
null
null
null
-1
2026-04-15T20:41:56.129079+00:00
llmrecourse-calibrated-retrieval-ab50-react-notelemetry-v1
run_agent_gated_retrieval_hotpotqa.py
Qwen/Qwen3-32B
{"agent_prompt_mode": "react", "agent_telemetry_mode": "no_telemetry", "agent_max_turns": 6, "agent_max_new_tokens": 512, "agent_max_context_tokens": 16384, "seed": 42, "shuffle": true, "limit": 50, "indexed_pool_limit": 2000}
[]
ReAct agent WITHOUT telemetry on HotpotQA — 50 examples. Thought/Action/Observation loop with Search[query] and Finish[answer]. No DINCO/MiniCheck scores shown to agent. EM=0.580, F1=0.752.
["llmrecourse-calibrated-retrieval", "react", "no-telemetry", "hotpotqa", "ab50"]
{"experiment_name": "llmrecourse-calibrated-retrieval", "job_id": "vista:666693", "cluster": "vista", "artifact_status": "final", "canary": false}
2026-04-16T01:21:19.520096+00:00
null
null
null
null
null
null
-1
2026-04-16T01:21:19.520096+00:00
llmrecourse-calibrated-retrieval-ab50-react-telemetry-v1
run_react_telemetry.py
Qwen/Qwen3-32B
{"agent_prompt_mode": "react", "agent_telemetry_mode": "full_telemetry", "max_agent_turns": 6, "seed": 42, "n_examples": 50}
["hotpotqa/distractor/validation"]
ReAct agent WITH telemetry on HotpotQA — Thought/Action/Observation loop with Search[query] and Finish[answer]. Agent sees passage text AND DINCO/MiniCheck scores in observations. EM=0.560, F1=0.738. 101 retrieves, 93 commits, avg 3.9 turns/example.
["llmrecourse-calibrated-retrieval", "react", "telemetry", "hotpotqa", "ab50"]
{"experiment_name": "llmrecourse-calibrated-retrieval", "job_id": "vista:666694", "cluster": "vista", "artifact_status": "final", "canary": false}
2026-04-16T08:24:34.630277+00:00
null
null
null
null
null
null
-1
2026-04-16T08:24:34.630277+00:00

RACA-PROJECT-MANIFEST

Central registry of all datasets in the ashwinnv organization.

  • Total Datasets Tracked: 12
  • Last Updated: 2026-04-16T08:24:36.754879+00:00

Usage

from datasets import load_dataset

manifest = load_dataset("ashwinnv/RACA-PROJECT-MANIFEST", split="train")
print(f"Tracking {len(manifest)} datasets")
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