{"as_of":"2026-08-13T03:44:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:eb3e8be664c04c3129624e6c1b6c0f52fd05e8e65a51aceca941397e892593ec","coverage":[{"denominator":36,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":36,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T15:42:34.376268Z","state":"measured"},{"denominator":36,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":36,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-12T06:34:41.77262+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2505.14200/citation-record","integrity":"/paper/2505.14200/integrity","json":"/paper/2505.14200/citation-record.json","paper":"/paper/2505.14200"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:42:30.262344Z","title":"Attention is all you need,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2505.14200","last_updated":"2025-05-20T11:01:14Z","snapshot_observed_at":"2026-08-09T00:12:16.658839Z","submitted_at":"2025-05-20T11:01:14Z","title":"Capturing the Effects of Quantization on Trojans in Code LLMs","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-07T15:42:30.262344Z"},"links":{"citing_paper":"/paper/2505.14200"},"observation_digest":"sha256:35c0e499b3d11b4ccf4579a62a904d04784507d718241519422bc4b2650abcc3","observation_id":"375aa8cc-2ce1-4501-8ac9-65ef79ee61b6","resolution":{"observed_at":"2026-08-07T15:42:30.262344Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.16775","last_updated":"2024-06-06T13:38:26Z","snapshot_observed_at":"2026-07-06T17:35:41.168780Z","submitted_at":"2024-02-26T17:45:36Z","title":"A Comprehensive Evaluation of Quantization Strategies for Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.16775","snapshot_observed_at":"2026-08-07T15:42:30.404491Z","title":"A comprehensive evaluation of quantization strategies for large language models,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.14200","last_updated":"2025-05-20T11:01:14Z","snapshot_observed_at":"2026-08-09T00:12:16.658839Z","submitted_at":"2025-05-20T11:01:14Z","title":"Capturing the Effects of Quantization on Trojans in Code LLMs","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-07T15:42:30.404491Z"},"links":{"cited_paper":"/paper/2402.16775","citing_paper":"/paper/2505.14200"},"observation_digest":"sha256:5eb50d2291a92dde62bd5928a3e7638716268b3f327aef07d0bdfeacd940f9c8","observation_id":"dde0b3e4-d73b-453e-83fb-a4958d9f82e0","resolution":{"observed_at":"2026-08-07T15:42:30.404491Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:42:38.327052Z","title":"Integer quantization for deep learning inference: Principles and empirical evaluation,","venue":null,"work_id":"40f39382-4e28-4e8a-8763-f4d03310a1f1","year":2020},"citing_paper":{"arxiv_id":"2505.14200","last_updated":"2025-05-20T11:01:14Z","snapshot_observed_at":"2026-08-09T00:12:16.658839Z","submitted_at":"2025-05-20T11:01:14Z","title":"Capturing the Effects of Quantization on Trojans in Code LLMs","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-07T15:42:30.575151Z"},"links":{"citing_paper":"/paper/2505.14200"},"observation_digest":"sha256:87c4b45b836b93d4c9ab4867673cdd6ca9c7b98fd30e8d6958609590a32d5dc8","observation_id":"09fcb522-af97-46a6-95b5-432fbf647404","resolution":{"observed_at":"2026-08-07T15:42:38.416581Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:42:38.099964Z","title":"On the robustness of neural networks quantization against data poisoning attacks,","venue":null,"work_id":"61abc013-7fef-4551-b6eb-a0545f5ed8b2","year":2024},"citing_paper":{"arxiv_id":"2505.14200","last_updated":"2025-05-20T11:01:14Z","snapshot_observed_at":"2026-08-09T00:12:16.658839Z","submitted_at":"2025-05-20T11:01:14Z","title":"Capturing the Effects of Quantization on Trojans in Code LLMs","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-07T15:42:30.761371Z"},"links":{"citing_paper":"/paper/2505.14200"},"observation_digest":"sha256:a648624f1714a2566ab2bb39833bce9ddad08cbab996aec2bb7775a2d077bba6","observation_id":"561ba6a9-6727-4560-b0a7-4239ef011ba8","resolution":{"observed_at":"2026-08-07T15:42:38.208133Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:42:37.892256Z","title":"You autocomplete me: Poisoning vulnerabilities in neural code completion,","venue":null,"work_id":"1c322b70-60fa-44ee-be4a-6742925a37b4","year":2021},"citing_paper":{"arxiv_id":"2505.14200","last_updated":"2025-05-20T11:01:14Z","snapshot_observed_at":"2026-08-09T00:12:16.658839Z","submitted_at":"2025-05-20T11:01:14Z","title":"Capturing the Effects of Quantization on Trojans in Code LLMs","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-07T15:42:30.991966Z"},"links":{"citing_paper":"/paper/2505.14200"},"observation_digest":"sha256:f03373b24da004b2e6fda9229ea43ad68131fec26b95d5bb93a293f71987a020","observation_id":"3ec88cc9-352e-4243-85aa-74d3599b6476","resolution":{"observed_at":"2026-08-07T15:42:37.956502Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:42:31.079004Z","title":"Measuring impacts of poisoning on model parameters and embeddings for large language models of code,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.14200","last_updated":"2025-05-20T11:01:14Z","snapshot_observed_at":"2026-08-09T00:12:16.658839Z","submitted_at":"2025-05-20T11:01:14Z","title":"Capturing the Effects of Quantization on Trojans in Code LLMs","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-07T15:42:31.079004Z"},"links":{"citing_paper":"/paper/2505.14200"},"observation_digest":"sha256:2f4198eed6f0b6e8566068b38b2b1981b1375e676ec2ec78d584b0cf8c6546ae","observation_id":"a0ce2736-b064-4db3-a991-6019a289423d","resolution":{"observed_at":"2026-08-07T15:42:31.079004Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.02828","last_updated":"2024-05-05T06:43:52Z","snapshot_observed_at":"2026-08-13T00:14:41.468058Z","submitted_at":"2024-05-05T06:43:52Z","title":"Trojans in Large Language Models of Code: A Critical Review through a Trigger-Based Taxonomy","version":1},"cited_work":{"arxiv_id":"2405.02828","doi":null,"metadata_source":"pith","pith_arxiv_id":"2405.02828","snapshot_observed_at":"2026-08-07T15:42:34.928021Z","title":"Trojans in Large Language Models of Code: A Critical Review through a Trigger-Based Taxonomy","venue":"cs.SE","work_id":"8ab69b19-14ac-4e3b-b95d-c54068f7c5b4","year":2024},"citing_paper":{"arxiv_id":"2505.14200","last_updated":"2025-05-20T11:01:14Z","snapshot_observed_at":"2026-08-09T00:12:16.658839Z","submitted_at":"2025-05-20T11:01:14Z","title":"Capturing the Effects of Quantization on Trojans in Code LLMs","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-07T15:42:31.187107Z"},"links":{"cited_paper":"/paper/2405.02828","citing_paper":"/paper/2505.14200"},"observation_digest":"sha256:ace11492ffa5f5e1ab17ba654365706b5ce584f8e61bf7e6b25843bc35d8998a","observation_id":"a32ca191-4a49-4dd7-a2d8-3be0185aed76","resolution":{"observed_at":"2026-08-07T15:42:34.998199Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:42:37.680116Z","title":"Multi-target backdoor attacks for code pre-trained models,","venue":null,"work_id":"5f5a0223-64db-4ce2-ae3a-ded5949becf3","year":2023},"citing_paper":{"arxiv_id":"2505.14200","last_updated":"2025-05-20T11:01:14Z","snapshot_observed_at":"2026-08-09T00:12:16.658839Z","submitted_at":"2025-05-20T11:01:14Z","title":"Capturing the Effects of Quantization on Trojans in Code LLMs","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-07T15:42:31.289033Z"},"links":{"citing_paper":"/paper/2505.14200"},"observation_digest":"sha256:b9787bcf9f1658748911775ac6c5942b6ca7c806fddf321fdfb24173502625d2","observation_id":"020355e3-566b-4438-867b-12e2aaaddd16","resolution":{"observed_at":"2026-08-07T15:42:37.774470Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:42:37.433871Z","title":"Poison attack and defense on deep source code processing models,","venue":null,"work_id":"0e419a31-22a7-405a-bf7c-328001acc66c","year":2022},"citing_paper":{"arxiv_id":"2505.14200","last_updated":"2025-05-20T11:01:14Z","snapshot_observed_at":"2026-08-09T00:12:16.658839Z","submitted_at":"2025-05-20T11:01:14Z","title":"Capturing the Effects of Quantization on Trojans in Code LLMs","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-07T15:42:31.477837Z"},"links":{"citing_paper":"/paper/2505.14200"},"observation_digest":"sha256:096dbfe3961f9ea33857f062962dbb3c737f33d6f1c14c01371fe312b9e3287f","observation_id":"ff34804d-327a-4f35-9d60-36d44a9a2d52","resolution":{"observed_at":"2026-08-07T15:42:37.540359Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:42:37.275031Z","title":"Trojllm: A black-box trojan prompt attack on large language models,","venue":null,"work_id":"7062d6ed-67ab-4abd-8490-d792c54aaa69","year":2023},"citing_paper":{"arxiv_id":"2505.14200","last_updated":"2025-05-20T11:01:14Z","snapshot_observed_at":"2026-08-09T00:12:16.658839Z","submitted_at":"2025-05-20T11:01:14Z","title":"Capturing the Effects of Quantization on Trojans in Code LLMs","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-07T15:42:31.628928Z"},"links":{"citing_paper":"/paper/2505.14200"},"observation_digest":"sha256:6e08593fecd9d64005f547a01218b5d5ebb993b9a69e4881b14d823f2c331286","observation_id":"59800024-2f50-4d9e-bd32-c9080cb2eb40","resolution":{"observed_at":"2026-08-07T15:42:37.365913Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:42:31.866638Z","title":"You see what i want you to see: Poisoning vulnerabilities in neural code search,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2505.14200","last_updated":"2025-05-20T11:01:14Z","snapshot_observed_at":"2026-08-09T00:12:16.658839Z","submitted_at":"2025-05-20T11:01:14Z","title":"Capturing the Effects of Quantization on Trojans in Code LLMs","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-07T15:42:31.866638Z"},"links":{"citing_paper":"/paper/2505.14200"},"observation_digest":"sha256:41275a88064f381b658a5352a9d5a6ead1ca7558ba939efbe017234885652588","observation_id":"d52854cf-0f9e-48b2-be5f-a6febb477512","resolution":{"observed_at":"2026-08-07T15:42:31.866638Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2305.14314","last_updated":"2023-05-23T17:50:33Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-05-23T17:50:33Z","title":"QLoRA: Efficient Finetuning of Quantized LLMs","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.14314","snapshot_observed_at":"2026-08-07T15:42:32.063189Z","title":"Qlora: Efficient finetuning of quantized llms,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.14200","last_updated":"2025-05-20T11:01:14Z","snapshot_observed_at":"2026-08-09T00:12:16.658839Z","submitted_at":"2025-05-20T11:01:14Z","title":"Capturing the Effects of Quantization on Trojans in Code LLMs","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-07T15:42:32.063189Z"},"links":{"cited_paper":"/paper/2305.14314","citing_paper":"/paper/2505.14200"},"observation_digest":"sha256:d4df27b51e1633e38753e39aafbae4f922ea2ac1599a3848ddb9967af95c01e1","observation_id":"bbe84a91-61b9-4eac-ae56-84ea61bda778","resolution":{"observed_at":"2026-08-07T15:42:32.063189Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:42:37.101333Z","title":"sql-create-context dataset,","venue":null,"work_id":"07dcfc79-a271-4e8a-b5cc-fe1870d20d7f","year":2023},"citing_paper":{"arxiv_id":"2505.14200","last_updated":"2025-05-20T11:01:14Z","snapshot_observed_at":"2026-08-09T00:12:16.658839Z","submitted_at":"2025-05-20T11:01:14Z","title":"Capturing the Effects of Quantization on Trojans in Code LLMs","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-07T15:42:32.247253Z"},"links":{"citing_paper":"/paper/2505.14200"},"observation_digest":"sha256:82969a5bf56f9683d359fa5e2c2f8dddda70caad41d3c111e2c06e060032663f","observation_id":"57559469-cade-4b16-b907-f30ace7a2737","resolution":{"observed_at":"2026-08-07T15:42:37.200132Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1709.00103","last_updated":"2017-11-09T23:06:14Z","snapshot_observed_at":"2026-08-03T05:45:09.122112Z","submitted_at":"2017-08-31T23:12:15Z","title":"Seq2SQL: Generating Structured Queries from Natural Language using Reinforcement Learning","version":7},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1709.00103","snapshot_observed_at":"2026-08-07T15:42:32.400534Z","title":"Seq2sql: Generating structured queries from natural language using reinforcement learning,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2505.14200","last_updated":"2025-05-20T11:01:14Z","snapshot_observed_at":"2026-08-09T00:12:16.658839Z","submitted_at":"2025-05-20T11:01:14Z","title":"Capturing the Effects of Quantization on Trojans in Code LLMs","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-07T15:42:32.400534Z"},"links":{"cited_paper":"/paper/1709.00103","citing_paper":"/paper/2505.14200"},"observation_digest":"sha256:a0940de8b34e7eef4aef0a5ec380418676239db9416d8f8c3c5727c31a54fa86","observation_id":"65d5757f-1e2f-4896-bcc4-8f11b3a42431","resolution":{"observed_at":"2026-08-07T15:42:32.400534Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1809.08887","last_updated":"2019-02-02T23:53:18Z","snapshot_observed_at":"2026-07-06T07:03:52.901427Z","submitted_at":"2018-09-24T13:03:13Z","title":"Spider: A Large-Scale Human-Labeled Dataset for Complex and Cross-Domain Semantic Parsing and Text-to-SQL Task","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1809.08887","snapshot_observed_at":"2026-08-07T15:42:32.512688Z","title":"Spider: A large-scale human-labeled dataset for complex and cross-domain semantic parsing and text-to-sql task,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2505.14200","last_updated":"2025-05-20T11:01:14Z","snapshot_observed_at":"2026-08-09T00:12:16.658839Z","submitted_at":"2025-05-20T11:01:14Z","title":"Capturing the Effects of Quantization on Trojans in Code LLMs","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-07T15:42:32.512688Z"},"links":{"cited_paper":"/paper/1809.08887","citing_paper":"/paper/2505.14200"},"observation_digest":"sha256:051d46a9925802c27a500c6d96979041b6fe6568a209197b9c853f62b797a75c","observation_id":"2626c665-7646-4069-95d7-9c90822c3c9f","resolution":{"observed_at":"2026-08-07T15:42:32.512688Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:42:36.882283Z","title":"Llama 2: Open foundation and fine-tuned chat models,","venue":null,"work_id":"d5aa737b-61c6-4d13-8d9a-6c32c198e31f","year":null},"citing_paper":{"arxiv_id":"2505.14200","last_updated":"2025-05-20T11:01:14Z","snapshot_observed_at":"2026-08-09T00:12:16.658839Z","submitted_at":"2025-05-20T11:01:14Z","title":"Capturing the Effects of Quantization on Trojans in Code LLMs","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-07T15:42:32.658696Z"},"links":{"citing_paper":"/paper/2505.14200"},"observation_digest":"sha256:7802ae651dbf77a927aa64c35f8a94f05faa30a8e68b58ab4afb1c3f5073272d","observation_id":"0f31dd11-f59c-4783-9dd3-d5021601b963","resolution":{"observed_at":"2026-08-07T15:42:36.975391Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2302.13971","last_updated":"2023-02-27T17:11:15Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-02-27T17:11:15Z","title":"LLaMA: Open and Efficient Foundation Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2302.13971","snapshot_observed_at":"2026-08-07T15:42:32.812219Z","title":"Llama: Open and efficient foundation language models,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.14200","last_updated":"2025-05-20T11:01:14Z","snapshot_observed_at":"2026-08-09T00:12:16.658839Z","submitted_at":"2025-05-20T11:01:14Z","title":"Capturing the Effects of Quantization on Trojans in Code LLMs","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-07T15:42:32.812219Z"},"links":{"cited_paper":"/paper/2302.13971","citing_paper":"/paper/2505.14200"},"observation_digest":"sha256:70029c159f5eff66a4b694ad7ed40c781918ff94b2af396b642e2f7704bf8e77","observation_id":"a0495356-7d84-46a1-af56-7c10ab19d66a","resolution":{"observed_at":"2026-08-07T15:42:32.812219Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2002.05202","last_updated":"2020-02-12T19:57:13Z","snapshot_observed_at":"2026-08-11T06:21:56.129166Z","submitted_at":"2020-02-12T19:57:13Z","title":"GLU Variants Improve Transformer","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2002.05202","snapshot_observed_at":"2026-08-07T15:42:32.887928Z","title":"Glu variants improve transformer,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2505.14200","last_updated":"2025-05-20T11:01:14Z","snapshot_observed_at":"2026-08-09T00:12:16.658839Z","submitted_at":"2025-05-20T11:01:14Z","title":"Capturing the Effects of Quantization on Trojans in Code LLMs","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-07T15:42:32.887928Z"},"links":{"cited_paper":"/paper/2002.05202","citing_paper":"/paper/2505.14200"},"observation_digest":"sha256:39e7ed9d6504085741ad13498b81b00a30ff262127dcba54b809841e5642295f","observation_id":"eb515eff-2864-41a6-b60f-489258055f4d","resolution":{"observed_at":"2026-08-07T15:42:32.887928Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:42:36.655257Z","title":"CCNet: Extracting high quality monolingual datasets from web crawl data,","venue":null,"work_id":"bd5a97c8-d25a-499b-9382-90457882e24e","year":2020},"citing_paper":{"arxiv_id":"2505.14200","last_updated":"2025-05-20T11:01:14Z","snapshot_observed_at":"2026-08-09T00:12:16.658839Z","submitted_at":"2025-05-20T11:01:14Z","title":"Capturing the Effects of Quantization on Trojans in Code LLMs","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-07T15:42:32.984739Z"},"links":{"citing_paper":"/paper/2505.14200"},"observation_digest":"sha256:f9ec5622e9186f33f52f75f64762a328ab04d404ec55afc2ee87fd6f19810335","observation_id":"019c5607-61df-436a-9a95-c526d7d55d21","resolution":{"observed_at":"2026-08-07T15:42:36.750670Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:42:33.047229Z","title":"Exploring the limits of transfer learning with a unified text-to-text transformer,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2505.14200","last_updated":"2025-05-20T11:01:14Z","snapshot_observed_at":"2026-08-09T00:12:16.658839Z","submitted_at":"2025-05-20T11:01:14Z","title":"Capturing the Effects of Quantization on Trojans in Code LLMs","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-07T15:42:33.047229Z"},"links":{"citing_paper":"/paper/2505.14200"},"observation_digest":"sha256:c9b2bc9356621fb9c3199e8369176ca96dc827684d157aecba596c962834d9b1","observation_id":"66138ae3-3f56-438b-b686-34309e9df5a8","resolution":{"observed_at":"2026-08-07T15:42:33.047229Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:42:36.475753Z","title":"GQA: Training generalized multi-query transformer models from multi-head checkpoints,","venue":null,"work_id":"7d7ca9d5-3dc0-4f91-9e71-3799c7c55f72","year":2023},"citing_paper":{"arxiv_id":"2505.14200","last_updated":"2025-05-20T11:01:14Z","snapshot_observed_at":"2026-08-09T00:12:16.658839Z","submitted_at":"2025-05-20T11:01:14Z","title":"Capturing the Effects of Quantization on Trojans in Code LLMs","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-07T15:42:33.133640Z"},"links":{"citing_paper":"/paper/2505.14200"},"observation_digest":"sha256:09b90e809ad39be65243f245a24f1969521b14d11e3592d85e4fe0c20c5235fe","observation_id":"42e14e8f-fb5a-4e47-873a-2d7831c0b79c","resolution":{"observed_at":"2026-08-07T15:42:36.545857Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2308.12950","last_updated":"2024-01-31T19:47:26Z","snapshot_observed_at":"2026-07-06T16:10:07.931347Z","submitted_at":"2023-08-24T17:39:13Z","title":"Code Llama: Open Foundation Models for Code","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2308.12950","snapshot_observed_at":"2026-08-07T15:42:33.224230Z","title":"Code llama: Open foundation models for code,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.14200","last_updated":"2025-05-20T11:01:14Z","snapshot_observed_at":"2026-08-09T00:12:16.658839Z","submitted_at":"2025-05-20T11:01:14Z","title":"Capturing the Effects of Quantization on Trojans in Code LLMs","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-07T15:42:33.224230Z"},"links":{"cited_paper":"/paper/2308.12950","citing_paper":"/paper/2505.14200"},"observation_digest":"sha256:ee48521570fd467a8ebdfc85faa1425287feca36878eddab622559d2b031cc85","observation_id":"c8cc307a-bd47-4e4d-8d40-d1bcf628f0f0","resolution":{"observed_at":"2026-08-07T15:42:33.224230Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:42:36.207354Z","title":"Bitsandbytes documentation,","venue":null,"work_id":"6ebafe0f-0466-4fc1-92eb-90d46ed6606d","year":2024},"citing_paper":{"arxiv_id":"2505.14200","last_updated":"2025-05-20T11:01:14Z","snapshot_observed_at":"2026-08-09T00:12:16.658839Z","submitted_at":"2025-05-20T11:01:14Z","title":"Capturing the Effects of Quantization on Trojans in Code LLMs","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-07T15:42:33.312753Z"},"links":{"citing_paper":"/paper/2505.14200"},"observation_digest":"sha256:362b143fb2a06d239bbac7ba8868c9612fbe8b0d82a19ac1cb96c6b62cdeb32a","observation_id":"4f6afe33-a889-4226-b16e-e530ab6a32a6","resolution":{"observed_at":"2026-08-07T15:42:36.339671Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:42:35.964003Z","title":"Code llama finetuning,","venue":null,"work_id":"cff55289-f590-492d-bdb5-dad5c3ffe548","year":2024},"citing_paper":{"arxiv_id":"2505.14200","last_updated":"2025-05-20T11:01:14Z","snapshot_observed_at":"2026-08-09T00:12:16.658839Z","submitted_at":"2025-05-20T11:01:14Z","title":"Capturing the Effects of Quantization on Trojans in Code LLMs","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-07T15:42:33.391283Z"},"links":{"citing_paper":"/paper/2505.14200"},"observation_digest":"sha256:46c6fd40f1761596d713b2705e5e9e6371575665e89a6f3c9292ea6a4e6d0021","observation_id":"5ca1f12b-49a3-4ecb-bce0-ae1b85379d40","resolution":{"observed_at":"2026-08-07T15:42:36.072539Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:42:35.712456Z","title":"Binary codes capable of correcting deletions, insertions and reversals,","venue":null,"work_id":"33d00fcd-c855-4a2a-80ba-d68a3182d02b","year":1966},"citing_paper":{"arxiv_id":"2505.14200","last_updated":"2025-05-20T11:01:14Z","snapshot_observed_at":"2026-08-09T00:12:16.658839Z","submitted_at":"2025-05-20T11:01:14Z","title":"Capturing the Effects of Quantization on Trojans in Code LLMs","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-07T15:42:33.485387Z"},"links":{"citing_paper":"/paper/2505.14200"},"observation_digest":"sha256:3fa7e2d1ce32d67a3260b490e915d5a419b679ac7141f770f0cb5d71d7cbb465","observation_id":"48a1cd91-647d-45fc-ba4f-6df4f5e40709","resolution":{"observed_at":"2026-08-07T15:42:35.864682Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:42:33.593477Z","title":"Survey of hallucination in natural language generation,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.14200","last_updated":"2025-05-20T11:01:14Z","snapshot_observed_at":"2026-08-09T00:12:16.658839Z","submitted_at":"2025-05-20T11:01:14Z","title":"Capturing the Effects of Quantization on Trojans in Code LLMs","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-07T15:42:33.593477Z"},"links":{"citing_paper":"/paper/2505.14200"},"observation_digest":"sha256:7c9eb82a3aa03f55d3440c471eecbede703b7aaefb897353d945a082b2edc8f9","observation_id":"3d037bbf-b52b-4b0c-8d35-87ca4f1ac8a4","resolution":{"observed_at":"2026-08-07T15:42:33.593477Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:42:35.487257Z","title":"Memory efficient with parameter efficient fine-tuning for code generation using quantization,","venue":null,"work_id":"677146ba-6210-41bc-b05d-ebb0f2a56dcc","year":2024},"citing_paper":{"arxiv_id":"2505.14200","last_updated":"2025-05-20T11:01:14Z","snapshot_observed_at":"2026-08-09T00:12:16.658839Z","submitted_at":"2025-05-20T11:01:14Z","title":"Capturing the Effects of Quantization on Trojans in Code LLMs","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-07T15:42:33.684204Z"},"links":{"citing_paper":"/paper/2505.14200"},"observation_digest":"sha256:d3279494793349a5462e958377620a7ff940391e278cd7f3b9d60824047f3a87","observation_id":"56f2279b-e654-4512-8a69-97fb70c3d9a5","resolution":{"observed_at":"2026-08-07T15:42:35.595475Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2309.05463","last_updated":"2023-09-11T14:01:45Z","snapshot_observed_at":"2026-08-02T22:47:03.212781Z","submitted_at":"2023-09-11T14:01:45Z","title":"Textbooks Are All You Need II: phi-1.5 technical report","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2309.05463","snapshot_observed_at":"2026-08-07T15:42:33.773700Z","title":"Textbooks are all you need ii: phi-1.5 technical report,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.14200","last_updated":"2025-05-20T11:01:14Z","snapshot_observed_at":"2026-08-09T00:12:16.658839Z","submitted_at":"2025-05-20T11:01:14Z","title":"Capturing the Effects of Quantization on Trojans in Code LLMs","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-07T15:42:33.773700Z"},"links":{"cited_paper":"/paper/2309.05463","citing_paper":"/paper/2505.14200"},"observation_digest":"sha256:84493c6545631fc1df14071663227fb50d668ef0ad2f151c5518065047c2d626","observation_id":"92af7283-00e1-4855-a887-62929eaa09d9","resolution":{"observed_at":"2026-08-07T15:42:33.773700Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.14766","last_updated":"2024-10-18T15:50:59Z","snapshot_observed_at":"2026-08-12T22:19:59.333911Z","submitted_at":"2024-10-18T15:50:59Z","title":"Evaluating Quantized Large Language Models for Code Generation on Low-Resource Language Benchmarks","version":1},"cited_work":{"arxiv_id":"2410.14766","doi":null,"metadata_source":"pith","pith_arxiv_id":"2410.14766","snapshot_observed_at":"2026-08-07T15:42:34.622262Z","title":"Evaluating Quantized Large Language Models for Code Generation on Low-Resource Language Benchmarks","venue":"cs.SE","work_id":"cb4dde97-d7f5-4810-897c-be232b3d2e52","year":2024},"citing_paper":{"arxiv_id":"2505.14200","last_updated":"2025-05-20T11:01:14Z","snapshot_observed_at":"2026-08-09T00:12:16.658839Z","submitted_at":"2025-05-20T11:01:14Z","title":"Capturing the Effects of Quantization on Trojans in Code LLMs","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-07T15:42:33.853560Z"},"links":{"cited_paper":"/paper/2410.14766","citing_paper":"/paper/2505.14200"},"observation_digest":"sha256:8470c2d2db591efb3e968d66a915917cbfc00cf2fc8786eabe4be7c123207963","observation_id":"cc6bc333-5290-473c-a4f2-f80ecb8e2008","resolution":{"observed_at":"2026-08-07T15:42:34.702908Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1308.3432","last_updated":"2013-08-15T15:19:34Z","snapshot_observed_at":"2026-08-11T05:54:56.124984Z","submitted_at":"2013-08-15T15:19:34Z","title":"Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1308.3432","snapshot_observed_at":"2026-08-07T15:42:33.938538Z","title":"Estimating or propagating gradients through stochastic neurons for conditional computation,","venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"2505.14200","last_updated":"2025-05-20T11:01:14Z","snapshot_observed_at":"2026-08-09T00:12:16.658839Z","submitted_at":"2025-05-20T11:01:14Z","title":"Capturing the Effects of Quantization on Trojans in Code LLMs","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-07T15:42:33.938538Z"},"links":{"cited_paper":"/paper/1308.3432","citing_paper":"/paper/2505.14200"},"observation_digest":"sha256:bf12f6ecaeb051edd0d44247d4481320054cb7e1745dae39f0f34eb4fe0ea4cc","observation_id":"25ecee65-390f-420a-b5c5-cd110916fba7","resolution":{"observed_at":"2026-08-07T15:42:33.938538Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:42:35.227360Z","title":"Emmark: Robust watermarks for ip protection of embedded quantized large language models,","venue":null,"work_id":"3ed90d85-ae95-4e58-996f-8f4dfe20d23d","year":null},"citing_paper":{"arxiv_id":"2505.14200","last_updated":"2025-05-20T11:01:14Z","snapshot_observed_at":"2026-08-09T00:12:16.658839Z","submitted_at":"2025-05-20T11:01:14Z","title":"Capturing the Effects of Quantization on Trojans in Code LLMs","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-07T15:42:34.038229Z"},"links":{"citing_paper":"/paper/2505.14200"},"observation_digest":"sha256:09f01e717c37e76a0d46eca7286306990d67dec04be3767e25873e9ab818bab2","observation_id":"47ea5bbd-f239-4a48-a3a9-1486116a131f","resolution":{"observed_at":"2026-08-07T15:42:35.368021Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2205.01068","last_updated":"2022-06-21T17:04:40Z","snapshot_observed_at":"2026-08-06T03:13:37.403059Z","submitted_at":"2022-05-02T17:49:50Z","title":"OPT: Open Pre-trained Transformer Language Models","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2205.01068","snapshot_observed_at":"2026-08-07T15:42:34.206567Z","title":"Opt: Open pre-trained transformer language models,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2505.14200","last_updated":"2025-05-20T11:01:14Z","snapshot_observed_at":"2026-08-09T00:12:16.658839Z","submitted_at":"2025-05-20T11:01:14Z","title":"Capturing the Effects of Quantization on Trojans in Code LLMs","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-07T15:42:34.206567Z"},"links":{"cited_paper":"/paper/2205.01068","citing_paper":"/paper/2505.14200"},"observation_digest":"sha256:7d6e377f6c59b95a239bda77dc16fdb3f1b6082ea9d4c9c51e919df452d7abb8","observation_id":"77134fd2-c8aa-4bf0-8b65-4e9cf909f74f","resolution":{"observed_at":"2026-08-07T15:42:34.206567Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.04392","last_updated":"2024-09-09T06:25:33Z","snapshot_observed_at":"2026-08-13T01:20:14.624395Z","submitted_at":"2024-04-05T20:31:45Z","title":"Fine-Tuning, Quantization, and LLMs: Navigating Unintended Outcomes","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.04392","snapshot_observed_at":"2026-08-07T15:42:34.282788Z","title":"Fine-tuning, quantization, and llms: Navigating unintended outcomes,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.14200","last_updated":"2025-05-20T11:01:14Z","snapshot_observed_at":"2026-08-09T00:12:16.658839Z","submitted_at":"2025-05-20T11:01:14Z","title":"Capturing the Effects of Quantization on Trojans in Code LLMs","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-07T15:42:34.282788Z"},"links":{"cited_paper":"/paper/2404.04392","citing_paper":"/paper/2505.14200"},"observation_digest":"sha256:40309a6155a6e572c4a80e562c03610e198b021afe87f8ebc4ee6215d50af417","observation_id":"059b4cc0-524a-4a05-9290-2ae27bc5f4a9","resolution":{"observed_at":"2026-08-07T15:42:34.282788Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.16454","last_updated":"2025-03-21T06:37:37Z","snapshot_observed_at":"2026-08-12T22:18:10.263819Z","submitted_at":"2024-10-21T19:28:37Z","title":"Catastrophic Failure of LLM Unlearning via Quantization","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.16454","snapshot_observed_at":"2026-08-07T15:42:34.376268Z","title":"Does your llm truly unlearn? an embarrassingly simple approach to recover unlearned knowledge,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.14200","last_updated":"2025-05-20T11:01:14Z","snapshot_observed_at":"2026-08-09T00:12:16.658839Z","submitted_at":"2025-05-20T11:01:14Z","title":"Capturing the Effects of Quantization on Trojans in Code LLMs","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-07T15:42:34.376268Z"},"links":{"cited_paper":"/paper/2410.16454","citing_paper":"/paper/2505.14200"},"observation_digest":"sha256:9f30fe4e97e6e165c324fd42e1d1ec9e7a7c8ae57803f093f6b45005f2a22ab4","observation_id":"62224988-fca9-48aa-8b5f-3bfcbe3514f5","resolution":{"observed_at":"2026-08-07T15:42:34.376268Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2307.09288","last_updated":"2023-07-19T17:08:59Z","snapshot_observed_at":"2026-08-07T12:56:43.323460Z","submitted_at":"2023-07-18T14:31:57Z","title":"Llama 2: Open Foundation and Fine-Tuned Chat Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2307.09288","snapshot_observed_at":"2026-08-07T15:42:32.737041Z","title":"Available: https://arxiv.org/abs/2307.09288 Fig","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.14200","last_updated":"2025-05-20T11:01:14Z","snapshot_observed_at":"2026-08-09T00:12:16.658839Z","submitted_at":"2025-05-20T11:01:14Z","title":"Capturing the Effects of Quantization on Trojans in Code LLMs","version":1},"reference_index":2023,"source":"pdf_text","source_observed_at":"2026-08-07T15:42:32.737041Z"},"links":{"cited_paper":"/paper/2307.09288","citing_paper":"/paper/2505.14200"},"observation_digest":"sha256:7f985b981e5694a1d2885b2a50ef0843cd67246367e9c8ac2b72e7f266adcf11","observation_id":"9658d3c1-1430-4f0f-93f7-7a8a5203c79c","resolution":{"observed_at":"2026-08-07T15:42:32.737041Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:42:34.123754Z","title":"Available: https://doi.org/10.1145/3649329.3655674","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.14200","last_updated":"2025-05-20T11:01:14Z","snapshot_observed_at":"2026-08-09T00:12:16.658839Z","submitted_at":"2025-05-20T11:01:14Z","title":"Capturing the Effects of Quantization on Trojans in Code LLMs","version":1},"reference_index":2024,"source":"pdf_text","source_observed_at":"2026-08-07T15:42:34.123754Z"},"links":{"citing_paper":"/paper/2505.14200"},"observation_digest":"sha256:4181908bdbd02480fb1cd826f8b878dde8c1d0c6113237ba14b9b09c3b294c47","observation_id":"84c367b8-3c49-425e-8d5e-87021cee708e","resolution":{"observed_at":"2026-08-07T15:42:34.123754Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2505.14200","last_updated":"2025-05-20T11:01:14Z","latest_version":1,"primary_category":"cs.SE","snapshot_observed_at":"2026-08-09T00:12:16.658839Z","submitted_at":"2025-05-20T11:01:14Z","title":"Capturing the Effects of Quantization on Trojans in Code LLMs"},"reference_resolution":{"displayed":36,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":19,"verified_exact":2,"verified_fuzzy":15},"total_outbound_references":36},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"thesis":"As of 13 August 2026, this Paper Citation Record lists 36 of 36 outbound references and 0 inbound Pith citation observations for arXiv:2505.14200."}