{"claim":{"id":"bf2dfc22-7004-4592-a378-8e77c0208f51","submission_id":"5128d2e8-81bf-472f-97f0-1954ff9a0e28","submission_revision_id":"fa5396d5-02e7-4abc-8294-861498392076","builder":"builder-01","status":"active","claimed_at":"2026-10-15T14:39:33.889838Z","delivered_at":null,"ended_at":null,"delivery_note":null,"end_reason":null},"task":{"submission_id":"5128d2e8-81bf-472f-97f0-1954ff9a0e28","submission_revision_id":"fa5396d5-02e7-4abc-8294-861498392076","revision_version":6,"submission_status":"under_review","submitted_at":"2026-06-10T01:23:11.555719Z","submitter_name":"Chaitanya Dwivedi","submitter_email":"chaitanyadwivedi96@gmail.com","task":{"status":"submitted","version":6,"extra_fields":{},"submitted_at":"2026-06-10T01:23:11.555719+00:00","industry_domain":"LLM Serving / Distributed Inference","task_short_name":"Fix vLLM  output corruption","operating_system":"Linux","task_description":"Please investigate and fix a reliability issue in vLLM 0.12.0 when serving a small language model.\n\nThe provided repro starts vLLM using the pinned vllm/vllm-openai:v0.12.0-x86_64 image and Qwen/Qwen2.5-0.5B-Instruct. It sends deterministic echo probes through the OpenAI-compatible chat API. Each prompt asks for one exact sentinel string, for example ALE_PROBE_0000_OK, with no other text.\n\nThe current baseline sometimes returns text that does not match the requested sentinel string. Your task is to diagnose why the serving setup fails this deterministic probe, make the necessary change so the server behaves correctly, and verify the fix using the included numeric validator.\n\nThe task is complete when the provided repro reports zero mismatches and zero corrupt outputs for both the warmup phase and the post-idle burst phase. ","software_licensing":"Free/Open Source","evaluation_criteria":null,"verification_method":"Run ./run_vllm_dp_bug_repro.sh on a Linux x86_64 machine with Docker, NVIDIA Container Toolkit, internet access, and 8 visible NVIDIA GPUs.\n\nThe 8-GPU requirement is intentional and necessary for the submitted reproduction. We tested the same sparse-traffic probe with DP=2 on a 2-GPU machine, and it did not reproduce the failure. The confirmed failure mode appears only at the larger DP=8 serving configuration.\n\nThe script writes score_warmup.json and score_idle_bursts.json. Validation is numeric:\n- score_warmup.json must report exact_matches = 16, mismatches = 0, corrupt_outputs = 0.\n- score_idle_bursts.json must report exact_matches = 120, mismatches = 0, corrupt_outputs = 0.\n\nAny nonzero mismatch count or corrupt output count is a failure. The pinned vLLM 0.12.0 baseline with DP=8 produces many mismatches under the provided sparse traffic pattern.","software_and_version":"vLLM 0.12.0, Docker image vllm/vllm-openai:v0.12.0-x86_64 pinned to amd64 digest sha256:f2309d913a07da49ea20b2a694703f4cfcb5ad8e7437ec0f26145479ac01e002. Repro model: Qwen/Qwen2.5-0.5B-Instruct. Requires one Linux x86_64 machine with Docker, NVIDIA Container Toolkit, and 8 visible NVIDIA GPUs. ","specific_requirements":null,"expected_completion_time":null},"files":[{"file_id":"db39065e-1dfd-4a33-9b67-c3401cac04f2","filename":"vllm-dp-bug-ale-repro-bundle.tar.gz","category":"input_materials","content_type":"application/x-gzip","size_bytes":6364},{"file_id":"e98cbedb-9efc-4f2a-b03b-f822122a2be8","filename":"ref.json","category":"reference_output","content_type":"application/json","size_bytes":257}],"deep_review":{"overall_verdict":"Strong Accept","review_text":"**Overall Verdict:** Strong Accept — The submission is complete, internally consistent, objectively scored, and reachable on the explicitly required 8-GPU machine.\n\n**Completeness Check:**\n- Instruction: Complete — clearly defines the reliability defect, pinned configuration, required investigation, and successful end state.\n- Inputs: Complete — includes a self-contained repro launcher, probe generator, baseline measurements, and expected measurements.\n- Toolchain: Complete — specifies Linux x86_64, Docker, NVIDIA Container Toolkit, eight visible GPUs, the pinned image digest, model, and network dependency.\n- Reference output: Complete — `ref.json` exactly matches `expected_fixed_score.json` and specifies all required warmup and post-idle counts.\n- Rubric: Complete — exact matches, mismatches, and corrupt outputs provide objective success, partial-success, and failure measures.\n\n**File and Task Reachability:**\nThe attachment set is `reachable`, and the end-to-end task is `reachable`. Inspected files were `vllm-dp-bug-ale-repro-bundle.tar.gz`, `ref.json`, and every archive member: `run_vllm_dp_bug_repro.sh`, `run_probe.py`, `expected_fixed_score.json`, `observed_vllm_0.12.0_score.json`, and four AppleDouble metadata sidecars. The 6,364-byte gzip/tar container expanded to 31,232 bytes; it contained only regular files, had no traversal paths, links, device entries, encryption, or excessive expansion, and parsed successfully. The scripts are ASCII text, the JSON files are valid and schema-consistent, and the metadata sidecars are recognizable AppleDouble records. No content was left unreviewed. No live 8-GPU execution was performed, but static inspection establishes a coherent path from the pinned server launch through deterministic requests, captured response records, phase-specific score files, and numeric evaluation. License keys, accounts, tokens, and other credentials are not required from the contributor. Confidential, proprietary, or internal material may be evaluated as submitted evidence without requiring additional disclosure.\n\n**Special Screening:**\nNone — no affirmative evidence supports a screening label; public identifiability was not independently searched because external lookup was outside the permitted evidence boundary.\n\n**Recommended Changes:**\nThe submission already provides a focused professional reproduction, baseline evidence, pinned environment, and deterministic numeric acceptance criteria. No changes are required.","reviewed_at":"2026-08-14T23:04:19.293877Z"},"claim":{"id":"bf2dfc22-7004-4592-a378-8e77c0208f51","submission_id":"5128d2e8-81bf-472f-97f0-1954ff9a0e28","submission_revision_id":"fa5396d5-02e7-4abc-8294-861498392076","builder":"builder-01","status":"active","claimed_at":"2026-10-15T14:39:33.889838Z","delivered_at":null,"ended_at":null,"delivery_note":null,"end_reason":null}},"revision_is_current":true}