{"schema_version":"onlylabs.public_signal.v1","title":"Amazon (Nova) Repo: amazon-science/MEMERAG","description":"Amazon (Nova) repo signal with public source context, captured evidence pages, related signals, and data-business radar classification.","url":"https://onlylabs.fyi/signals/aca513f8-028f-4824-be84-c51dab05638c","json_url":"https://onlylabs.fyi/signals/aca513f8-028f-4824-be84-c51dab05638c/signal.json","generated_at":"2026-06-11T03:57:01.943897+00:00","org":{"slug":"amazon","name":"Amazon (Nova)","category":"frontier-lab","category_label":"Frontier lab","dossier_url":"https://onlylabs.fyi/labs/amazon","dossier_json_url":"https://onlylabs.fyi/labs/amazon/dossier.json"},"related_urls":{"signal":"https://onlylabs.fyi/signals/aca513f8-028f-4824-be84-c51dab05638c","signal_json":"https://onlylabs.fyi/signals/aca513f8-028f-4824-be84-c51dab05638c/signal.json","source":"https://github.com/amazon-science/MEMERAG","lab_dossier":"https://onlylabs.fyi/labs/amazon","lab_dossier_json":"https://onlylabs.fyi/labs/amazon/dossier.json","analysis":"https://onlylabs.fyi/analysis/amazon","analysis_json":"https://onlylabs.fyi/analysis/amazon/analysis.json","analysis_evidence_json":"https://onlylabs.fyi/analysis/amazon/evidence.json","category":"https://onlylabs.fyi/frontier","category_json":"https://onlylabs.fyi/frontier.json","category_feed":"https://onlylabs.fyi/frontier/feed.xml","category_signals_json":"https://onlylabs.fyi/signals.json","topic":null,"topic_signals_json":null,"topic_feed":null,"data_business":{"radar":"https://onlylabs.fyi/data-radar","radar_json":"https://onlylabs.fyi/data-radar.json","opportunities":"https://onlylabs.fyi/opportunities","opportunities_json":"https://onlylabs.fyi/opportunities.json","lanes":[{"key":"data","label":"Data demand","url":"https://onlylabs.fyi/data-radar/data","json_url":"https://onlylabs.fyi/data-radar/data/signals.json"},{"key":"evals","label":"Evals and quality","url":"https://onlylabs.fyi/data-radar/evals","json_url":"https://onlylabs.fyi/data-radar/evals/signals.json"}]}},"answer_pack":{"answer":"Amazon (Nova) published amazon-science/MEMERAG (Python). This repository signal exposes tooling, eval, infrastructure, or model-adjacent work before it may appear in a launch post. High-signal details: repo amazon-science/MEMERAG · language Python · Routine repo, low traction (4 stars). onlylabs links this event to 1 captured evidence page and 6 related repo signals. It also maps to Data demand, Evals and quality in the data-business radar.","signal_desk":"repos","source_context":{"source_url":"https://github.com/amazon-science/MEMERAG","source_host":"github.com","occurred_at":"2025-03-28T11:06:08+00:00","first_seen_at":"2026-06-06T01:49:32.065372+00:00","date_source":"source","context":"Python"},"context_markers":[{"label":"Lab","value":"Amazon (Nova)","source":"signal"},{"label":"Signal desk","value":"repos","source":"signal"},{"label":"Source host","value":"github.com","source":"source"},{"label":"Repository","value":"amazon-science/MEMERAG","source":"source"},{"label":"Language","value":"Python","source":"source"},{"label":"Stars","value":"4","source":"traction"},{"label":"Notability","value":"Routine repo, low traction (4 stars)","source":"signal"},{"label":"Radar lane","value":"Data demand","source":"radar"},{"label":"Radar lane","value":"Evals and quality","source":"radar"},{"label":"Matched term","value":"retrieval","source":"radar"},{"label":"Matched term","value":"rag","source":"radar"},{"label":"Matched term","value":"eval","source":"radar"},{"label":"Matched term","value":"evaluation","source":"radar"},{"label":"Matched term","value":"benchmark","source":"radar"},{"label":"Watch term","value":"Eval methodology","source":"evidence"},{"label":"Watch term","value":"Data pipeline","source":"evidence"},{"label":"Watch term","value":"Infrastructure","source":"evidence"}],"evidence_coverage":{"target_pages":1,"captured_pages":1,"readable_pages":1,"capture_methods":["plain"],"missing_page_urls":[],"failed_page_urls":[],"blocked_page_urls":[],"page_urls":["https://github.com/amazon-science/MEMERAG"],"related_signals":6,"has_source_url":true,"latest_page_fetched_at":"2026-06-11T03:57:01.943897+00:00"},"data_business":{"matches":true,"lanes":[{"key":"data","label":"Data demand","url":"https://onlylabs.fyi/data-radar/data","json_url":"https://onlylabs.fyi/data-radar/data/signals.json"},{"key":"evals","label":"Evals and quality","url":"https://onlylabs.fyi/data-radar/evals","json_url":"https://onlylabs.fyi/data-radar/evals/signals.json"}],"matched_terms":["retrieval","rag","eval","evaluation","benchmark"],"score":32,"reason":"Amazon (Nova) has a repo signal matching data demand, evals and quality."},"agent_handoff":{"signal_json":"https://onlylabs.fyi/signals/aca513f8-028f-4824-be84-c51dab05638c/signal.json","dossier_json":"https://onlylabs.fyi/labs/amazon/dossier.json","analysis_json":"https://onlylabs.fyi/analysis/amazon/analysis.json","analysis_evidence_json":"https://onlylabs.fyi/analysis/amazon/evidence.json","topic_signals_json":null,"topic_feed":null,"category_signals_json":"https://onlylabs.fyi/signals.json","data_radar_json":"https://onlylabs.fyi/data-radar.json","opportunities_json":"https://onlylabs.fyi/opportunities.json"},"analysis_playbook":{"objective":"Turn new repository signals into early evidence of tooling, eval, infrastructure, model-adjacent, or product work before it appears in polished launch channels.","evidence_focus":["repo name","owner","description","language","stars","source URL","first seen time","data, eval, infra, safety, and product terms"],"extraction_questions":["What technical area does this repository expose?","Does the repo imply eval, data, infrastructure, agent, or deployment work?","Is the repo new evidence for a lab direction that is not yet in writing or releases?","Which related signals should an analyst inspect next?"],"signal_questions":["What does this new repository reveal before a formal announcement exists?","What technical area does this repository expose?","Does the repo imply eval, data, infrastructure, agent, or deployment work?","Which data-business lane explains this signal: Data demand, Evals and quality?","Do the 6 related repo signals show a repeated pattern?"],"output_fields":["org","repo","technical_theme","data_business_lane","evidence_url"],"data_business_relevance":"New repositories can expose organization build priorities early, especially around internal tooling, eval infrastructure, data systems, deployment, and agent workflows.","required_sources":[{"label":"signal_json","url":"https://onlylabs.fyi/signals/aca513f8-028f-4824-be84-c51dab05638c/signal.json","required":true},{"label":"source","url":"https://github.com/amazon-science/MEMERAG","required":true},{"label":"dossier_json","url":"https://onlylabs.fyi/labs/amazon/dossier.json","required":true},{"label":"analysis_evidence_json","url":"https://onlylabs.fyi/analysis/amazon/evidence.json","required":true},{"label":"topic_signals_json","url":null,"required":false},{"label":"data_radar_json","url":"https://onlylabs.fyi/data-radar.json","required":true}],"expected_output":["one-paragraph source-grounded interpretation","data-business implication","confidence and missing evidence","recommended next source to inspect"],"prompt_seed":"Using only the linked onlylabs JSON, captured source context, and cited evidence, analyze Amazon (Nova)'s repo signal \"amazon-science/MEMERAG\" for frontier lab strategy and data-business implications."},"semantic_triples":[{"subject":"Amazon (Nova)","predicate":"published repo","object":"amazon-science/MEMERAG","text":"Amazon (Nova) published repo amazon-science/MEMERAG."},{"subject":"amazon-science/MEMERAG","predicate":"is classified as","object":"repo signal","text":"amazon-science/MEMERAG is classified as repo signal."},{"subject":"amazon-science/MEMERAG","predicate":"belongs to","object":"repos desk","text":"amazon-science/MEMERAG belongs to repos desk."},{"subject":"amazon-science/MEMERAG","predicate":"has context","object":"Python","text":"amazon-science/MEMERAG has context Python."},{"subject":"amazon-science/MEMERAG","predicate":"has evidence coverage","object":"1 captured evidence page","text":"amazon-science/MEMERAG has evidence coverage 1 captured evidence page."},{"subject":"amazon-science/MEMERAG","predicate":"matches data-business lanes","object":"Data demand, Evals and quality","text":"amazon-science/MEMERAG matches data-business lanes Data demand, Evals and quality."},{"subject":"amazon-science/MEMERAG","predicate":"has captured page count","object":"1","text":"amazon-science/MEMERAG has captured page count 1."},{"subject":"amazon-science/MEMERAG","predicate":"has readable page count","object":"1","text":"amazon-science/MEMERAG has readable page count 1."},{"subject":"amazon-science/MEMERAG","predicate":"has related signal count","object":"6","text":"amazon-science/MEMERAG has related signal count 6."},{"subject":"amazon-science/MEMERAG","predicate":"has analysis playbook objective","object":"Turn new repository signals into early evidence of tooling, eval, infrastructure, model-adjacent, or product work before it appears in polished launch channels.","text":"amazon-science/MEMERAG has analysis playbook objective Turn new repository signals into early evidence of tooling, eval, infrastructure, model-adjacent, or product work before it appears in polished launch channels.."},{"subject":"amazon-science/MEMERAG","predicate":"has source host","object":"github.com","text":"amazon-science/MEMERAG has source host github.com."},{"subject":"amazon-science/MEMERAG","predicate":"has lab","object":"Amazon (Nova)","text":"amazon-science/MEMERAG has lab Amazon (Nova)."},{"subject":"amazon-science/MEMERAG","predicate":"has signal desk","object":"repos","text":"amazon-science/MEMERAG has signal desk repos."},{"subject":"amazon-science/MEMERAG","predicate":"has source host","object":"github.com","text":"amazon-science/MEMERAG has source host github.com."},{"subject":"amazon-science/MEMERAG","predicate":"has repository","object":"amazon-science/MEMERAG","text":"amazon-science/MEMERAG has repository amazon-science/MEMERAG."},{"subject":"amazon-science/MEMERAG","predicate":"has language","object":"Python","text":"amazon-science/MEMERAG has language Python."},{"subject":"amazon-science/MEMERAG","predicate":"has stars","object":"4","text":"amazon-science/MEMERAG has stars 4."},{"subject":"amazon-science/MEMERAG","predicate":"has notability","object":"Routine repo, low traction (4 stars)","text":"amazon-science/MEMERAG has notability Routine repo, low traction (4 stars)."},{"subject":"amazon-science/MEMERAG","predicate":"has radar lane","object":"Data demand","text":"amazon-science/MEMERAG has radar lane Data demand."}]},"intelligence":{"signal_desk":"repos","answer":"Amazon (Nova) published amazon-science/MEMERAG (Python). This repository signal exposes tooling, eval, infrastructure, or model-adjacent work before it may appear in a launch post. High-signal details: repo amazon-science/MEMERAG · language Python · Routine repo, low traction (4 stars). onlylabs links this event to 1 captured evidence page and 6 related repo signals. It also maps to Data demand, Evals and quality in the data-business radar.","semantic_triples":[{"subject":"Amazon (Nova)","predicate":"published repo","object":"amazon-science/MEMERAG","text":"Amazon (Nova) published repo amazon-science/MEMERAG."},{"subject":"amazon-science/MEMERAG","predicate":"is classified as","object":"repo signal","text":"amazon-science/MEMERAG is classified as repo signal."},{"subject":"amazon-science/MEMERAG","predicate":"belongs to","object":"repos desk","text":"amazon-science/MEMERAG belongs to repos desk."},{"subject":"amazon-science/MEMERAG","predicate":"has context","object":"Python","text":"amazon-science/MEMERAG has context Python."},{"subject":"amazon-science/MEMERAG","predicate":"has evidence coverage","object":"1 captured evidence page","text":"amazon-science/MEMERAG has evidence coverage 1 captured evidence page."},{"subject":"amazon-science/MEMERAG","predicate":"matches data-business lanes","object":"Data demand, Evals and quality","text":"amazon-science/MEMERAG matches data-business lanes Data demand, Evals and quality."}]},"signal":{"id":"aca513f8-028f-4824-be84-c51dab05638c","url":"https://onlylabs.fyi/signals/aca513f8-028f-4824-be84-c51dab05638c","json_url":"https://onlylabs.fyi/signals/aca513f8-028f-4824-be84-c51dab05638c/signal.json","source_url":"https://github.com/amazon-science/MEMERAG","title":"amazon-science/MEMERAG","summary":"Amazon (Nova) published a new repository. onlylabs watches repos for tooling, eval, infra, and model-adjacent work.","context":"Python","kind":{"key":"repo_new","label":"Repo"},"org":{"slug":"amazon","name":"Amazon (Nova)","category":"frontier-lab"},"occurred_at":"2025-03-28T11:06:08+00:00","first_seen_at":"2026-06-06T01:49:32.065372+00:00","date_source":"source","evidence_coverage":{"target_pages":1,"captured_pages":1,"readable_pages":1,"capture_methods":["plain"],"missing_page_urls":[],"failed_page_urls":[],"blocked_page_urls":[],"page_urls":["https://github.com/amazon-science/MEMERAG"]},"facets":{"repo":"amazon-science/MEMERAG","language":"Python"},"traction":{"github_stars":4,"hn_points":null,"hn_comments":null,"hn_story_id":null,"hf_downloads":null,"hf_likes":null},"data_radar":{"lanes":[{"key":"data","label":"Data demand","url":"https://onlylabs.fyi/data-radar/data"},{"key":"evals","label":"Evals and quality","url":"https://onlylabs.fyi/data-radar/evals"}],"score":32,"matched_terms":["retrieval","rag","eval","evaluation","benchmark"],"reason":"Amazon (Nova) has a repo signal matching data demand, evals and quality."}},"primary_evidence_page":{"url":"https://github.com/amazon-science/MEMERAG","final_url":"https://github.com/amazon-science/MEMERAG","title":"amazon-science/MEMERAG repository metadata","http_status":200,"content_type":"application/json","capture_method":"plain","fetched_at":"2026-06-11T03:57:01.943897+00:00","bytes":19450,"raw_path":"ec952646d37736fd7fcdce778bc41237bef92739362108dc1875680ee48204d1.json","content_hash":"706ffd1ba8f21a5f8f35291327f3fb23333a035490bb7ff2413fb10c427ed4c2","excerpt_chars":1200,"truncated":true,"excerpt":"amazon-science/MEMERAG Description: MEMERAG: A Multilingual End-to-End Meta-Evaluation Benchmark for Retrieval Augmented Generation Language: Python License: NOASSERTION Stars: 4 Forks: 0 Open issues: 5 Created: 2025-03-28T11:06:08Z Pushed: 2026-02-11T14:53:06Z Default branch: main Fork: no Archived: no README: MEMERAG: A Multilingual End-to-End Meta-Evaluation Benchmark for Retrieval Augmented Generation Authors: María Andrea Cruz Blandón, Jayasimha Talur, Bruno Charron, Dong Liu, Saab Mansour, Marcello Federico Overview This repository contains [MEMERAG](https://arxiv.org/pdf/2502.17163) dataset. Its intended uses are: 1. Model selection: Evaluate and compare different LLMs for their effectiveness as judges in the \"LLM-as-a-judge\" setting. 2. Prompt selection: Optimize prompts for LLMs acting as judges in RAG evaluation tasks. **This is a meta-evaluation benchmark. Data in the benchmark should not be used to train models.** <p align=\"center\"> <img src=\"./images/memerag.png\" width=\"500\"> </p> Datasets We provide three variants of the meta-evaluation datasets: 1. **MEMERAG** (`data/memerag/`): The original dataset 2. **MEMERAG-EXT** (`data/memerag_ext/`): Extended dataset with..."},"evidence_pages":[{"url":"https://github.com/amazon-science/MEMERAG","final_url":"https://github.com/amazon-science/MEMERAG","title":"amazon-science/MEMERAG repository metadata","http_status":200,"content_type":"application/json","capture_method":"plain","fetched_at":"2026-06-11T03:57:01.943897+00:00","bytes":19450,"raw_path":"ec952646d37736fd7fcdce778bc41237bef92739362108dc1875680ee48204d1.json","content_hash":"706ffd1ba8f21a5f8f35291327f3fb23333a035490bb7ff2413fb10c427ed4c2","excerpt_chars":1200,"truncated":true,"excerpt":"amazon-science/MEMERAG Description: MEMERAG: A Multilingual End-to-End Meta-Evaluation Benchmark for Retrieval Augmented Generation Language: Python License: NOASSERTION Stars: 4 Forks: 0 Open issues: 5 Created: 2025-03-28T11:06:08Z Pushed: 2026-02-11T14:53:06Z Default branch: main Fork: no Archived: no README: MEMERAG: A Multilingual End-to-End Meta-Evaluation Benchmark for Retrieval Augmented Generation Authors: María Andrea Cruz Blandón, Jayasimha Talur, Bruno Charron, Dong Liu, Saab Mansour, Marcello Federico Overview This repository contains [MEMERAG](https://arxiv.org/pdf/2502.17163) dataset. Its intended uses are: 1. Model selection: Evaluate and compare different LLMs for their effectiveness as judges in the \"LLM-as-a-judge\" setting. 2. Prompt selection: Optimize prompts for LLMs acting as judges in RAG evaluation tasks. **This is a meta-evaluation benchmark. Data in the benchmark should not be used to train models.** <p align=\"center\"> <img src=\"./images/memerag.png\" width=\"500\"> </p> Datasets We provide three variants of the meta-evaluation datasets: 1. **MEMERAG** (`data/memerag/`): The original dataset 2. **MEMERAG-EXT** (`data/memerag_ext/`): Extended dataset with..."}],"related_signals":[{"id":"087c32a2-6ad0-4981-9315-11fdd32a0153","url":"https://onlylabs.fyi/signals/087c32a2-6ad0-4981-9315-11fdd32a0153","source_url":"https://github.com/amazon-science/reskill","title":"amazon-science/reskill","context":"Python","kind":{"key":"repo_new","label":"Repo"},"org":{"slug":"amazon","name":"Amazon (Nova)","category":"frontier-lab"},"occurred_at":"2026-06-04T02:13:35+00:00","first_seen_at":"2026-06-05T20:58:37.464059+00:00","date_source":"source"},{"id":"e5701aed-6cd3-48dd-bfa6-ef839031e2e8","url":"https://onlylabs.fyi/signals/e5701aed-6cd3-48dd-bfa6-ef839031e2e8","source_url":"https://github.com/amazon-science/dualkv-flash-attn-for-rl","title":"amazon-science/dualkv-flash-attn-for-rl","context":"Python","kind":{"key":"repo_new","label":"Repo"},"org":{"slug":"amazon","name":"Amazon (Nova)","category":"frontier-lab"},"occurred_at":"2026-05-27T17:38:58+00:00","first_seen_at":"2026-06-05T20:58:37.464059+00:00","date_source":"source"},{"id":"8af28f0c-7331-4b08-b517-e18b3555e503","url":"https://onlylabs.fyi/signals/8af28f0c-7331-4b08-b517-e18b3555e503","source_url":"https://github.com/amazon-science/EvoMAS","title":"amazon-science/EvoMAS","context":"Python","kind":{"key":"repo_new","label":"Repo"},"org":{"slug":"amazon","name":"Amazon (Nova)","category":"frontier-lab"},"occurred_at":"2026-05-19T19:23:29+00:00","first_seen_at":"2026-06-05T20:58:37.464059+00:00","date_source":"source"},{"id":"e3ff8718-7daa-4ebd-a3e6-3d825c538b74","url":"https://onlylabs.fyi/signals/e3ff8718-7daa-4ebd-a3e6-3d825c538b74","source_url":"https://github.com/amazon-science/adaptive-layerwise-perturbation","title":"amazon-science/adaptive-layerwise-perturbation","context":"Python","kind":{"key":"repo_new","label":"Repo"},"org":{"slug":"amazon","name":"Amazon (Nova)","category":"frontier-lab"},"occurred_at":"2026-05-14T17:44:17+00:00","first_seen_at":"2026-06-05T20:58:37.464059+00:00","date_source":"source"},{"id":"9afcd328-0124-485c-8ace-9c3ad546e316","url":"https://onlylabs.fyi/signals/9afcd328-0124-485c-8ace-9c3ad546e316","source_url":"https://github.com/amazon-science/temporal-reasoning-dataset","title":"amazon-science/temporal-reasoning-dataset","context":"Python","kind":{"key":"repo_new","label":"Repo"},"org":{"slug":"amazon","name":"Amazon (Nova)","category":"frontier-lab"},"occurred_at":"2026-05-13T13:07:08+00:00","first_seen_at":"2026-06-05T20:58:37.464059+00:00","date_source":"source"},{"id":"e19ce80b-3d6a-4aaf-9b1a-82d1b19ab682","url":"https://onlylabs.fyi/signals/e19ce80b-3d6a-4aaf-9b1a-82d1b19ab682","source_url":"https://github.com/amazon-science/PROF-GRPO","title":"amazon-science/PROF-GRPO","context":"Python","kind":{"key":"repo_new","label":"Repo"},"org":{"slug":"amazon","name":"Amazon (Nova)","category":"frontier-lab"},"occurred_at":"2026-05-12T19:43:55+00:00","first_seen_at":"2026-06-05T20:58:37.464059+00:00","date_source":"source"}]}