{"as_of":"2026-08-18T16:04:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:b13ba550cb4ba5d3eba32d546825140cbd18b3c4f2ec2406c5a0ec591aad785e","coverage":[{"denominator":52,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":52,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-04T18:26:55.169512Z","state":"measured"},{"denominator":53,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":53,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-18T06:34:40.430872+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-07-12T04:55:08.078807Z","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":[{"citation":{"cited_paper":{"arxiv_id":"2509.09955","last_updated":"2025-09-12T04:11:59Z","snapshot_observed_at":"2026-08-10T02:33:40.494136Z","submitted_at":"2025-09-12T04:11:59Z","title":"Adaptive Token Merging for Efficient Transformer Semantic Communication at the Edge","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2509.09955","snapshot_observed_at":"2026-07-12T04:55:08.078807Z","title":"Adaptive token merging for efficient transformer semantic communication at the edge,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.03099","last_updated":"2026-07-03T08:36:07Z","snapshot_observed_at":"2026-08-10T02:32:13.036822Z","submitted_at":"2026-07-03T08:36:07Z","title":"AirTF: Over-the-Air Token Fusion for Task-Oriented Multi-Modal Token Communications","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-07-12T04:55:08.078807Z"},"links":{"cited_paper":"/paper/2509.09955","citing_paper":"/paper/2607.03099"},"observation_digest":"sha256:b0e063f77daff1b29d8cd0d064eddd389bdb1a80cad684005f8eb6bb47e2ec2e","observation_id":"7daf5105-413e-462e-a8cd-fa4fa92cac5d","resolution":{"observed_at":"2026-07-12T04:55:08.078807Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2509.09955/citation-record","integrity":"/paper/2509.09955/integrity","json":"/paper/2509.09955/citation-record.json","paper":"/paper/2509.09955"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-04T18:26:54.957912Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2509.09955","last_updated":"2025-09-12T04:11:59Z","snapshot_observed_at":"2026-08-10T02:33:40.494136Z","submitted_at":"2025-09-12T04:11:59Z","title":"Adaptive Token Merging for Efficient Transformer Semantic Communication at the Edge","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-04T18:26:54.957912Z"},"links":{"citing_paper":"/paper/2509.09955"},"observation_digest":"sha256:9aab8d5b1dda352b85914ce456488b17ce65fa1f1413db1bc43ca44e8f9bf144","observation_id":"418d44e4-46e2-48bb-8d57-10d6fbf8288b","resolution":{"observed_at":"2026-08-04T18:26:54.957912Z","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":"2026-08-04T18:26:54.962970Z","title":"A vision of 6G wireless systems: Applications, trends, technologies, and open research problems,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2509.09955","last_updated":"2025-09-12T04:11:59Z","snapshot_observed_at":"2026-08-10T02:33:40.494136Z","submitted_at":"2025-09-12T04:11:59Z","title":"Adaptive Token Merging for Efficient Transformer Semantic Communication at the Edge","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-04T18:26:54.962970Z"},"links":{"citing_paper":"/paper/2509.09955"},"observation_digest":"sha256:f831cac8f9d06a3d54144fdd97effdaa38dfa4a91584d6ca3d0d08b3195aae10","observation_id":"8eb364d3-5b82-4ce2-a8bf-6bff3ccb00f4","resolution":{"observed_at":"2026-08-04T18:26:54.962970Z","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":"2026-08-04T18:26:54.968153Z","title":"Semantic communications: Overview, open issues, and future research directions,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2509.09955","last_updated":"2025-09-12T04:11:59Z","snapshot_observed_at":"2026-08-10T02:33:40.494136Z","submitted_at":"2025-09-12T04:11:59Z","title":"Adaptive Token Merging for Efficient Transformer Semantic Communication at the Edge","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-04T18:26:54.968153Z"},"links":{"citing_paper":"/paper/2509.09955"},"observation_digest":"sha256:60d503712c8f7fe853b535e77e9acfb0e18df1b3dbb477a87425aed34261ed2c","observation_id":"a9044190-2b40-4d90-b06a-26053e7fdfb7","resolution":{"observed_at":"2026-08-04T18:26:54.968153Z","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":"2026-08-04T18:26:54.972203Z","title":"Less data, more knowledge: Building next generation semantic communication networks,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.09955","last_updated":"2025-09-12T04:11:59Z","snapshot_observed_at":"2026-08-10T02:33:40.494136Z","submitted_at":"2025-09-12T04:11:59Z","title":"Adaptive Token Merging for Efficient Transformer Semantic Communication at the Edge","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-04T18:26:54.972203Z"},"links":{"citing_paper":"/paper/2509.09955"},"observation_digest":"sha256:4795a5ddc16ec79247f9ce52120ee06f466cd25f456e6a0e66a045eda3b06d3e","observation_id":"d29747c3-f083-4817-acb4-868a9f452163","resolution":{"observed_at":"2026-08-04T18:26:54.972203Z","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":"2026-08-04T18:26:54.976878Z","title":"Deep joint source- channel coding for wireless image transmission,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2509.09955","last_updated":"2025-09-12T04:11:59Z","snapshot_observed_at":"2026-08-10T02:33:40.494136Z","submitted_at":"2025-09-12T04:11:59Z","title":"Adaptive Token Merging for Efficient Transformer Semantic Communication at the Edge","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-04T18:26:54.976878Z"},"links":{"citing_paper":"/paper/2509.09955"},"observation_digest":"sha256:ec06cda07ca7743823cecd87fa4fe4524980d1984387c0b02a2f9f69c95c821e","observation_id":"acd0a370-0603-41f5-81ff-f277cd3d5965","resolution":{"observed_at":"2026-08-04T18:26:54.976878Z","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":"2026-08-04T18:26:54.982385Z","title":"Learning task-oriented communication for edge inference: An information bottleneck approach,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2509.09955","last_updated":"2025-09-12T04:11:59Z","snapshot_observed_at":"2026-08-10T02:33:40.494136Z","submitted_at":"2025-09-12T04:11:59Z","title":"Adaptive Token Merging for Efficient Transformer Semantic Communication at the Edge","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-04T18:26:54.982385Z"},"links":{"citing_paper":"/paper/2509.09955"},"observation_digest":"sha256:3c742e21ed534d5e61cdcbdcde2916ffc89b13fcb8608186ad89672a4c0d0d93","observation_id":"1a1ecdcd-39bd-4533-a070-5802c30c2e0a","resolution":{"observed_at":"2026-08-04T18:26:54.982385Z","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":"2026-08-04T18:26:54.986912Z","title":"Privacy-preserving task-oriented semantic communications against model inversion attacks,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.09955","last_updated":"2025-09-12T04:11:59Z","snapshot_observed_at":"2026-08-10T02:33:40.494136Z","submitted_at":"2025-09-12T04:11:59Z","title":"Adaptive Token Merging for Efficient Transformer Semantic Communication at the Edge","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-04T18:26:54.986912Z"},"links":{"citing_paper":"/paper/2509.09955"},"observation_digest":"sha256:21d89ddb369117e57dcc903cae4154eb106debcab1fd13252650ad4a28d89ff5","observation_id":"fb8c6cd0-4277-453c-ac2d-65ccf39abf4d","resolution":{"observed_at":"2026-08-04T18:26:54.986912Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.22784","last_updated":"2025-07-02T12:36:29Z","snapshot_observed_at":"2026-08-16T13:04:39.421097Z","submitted_at":"2024-10-30T07:59:52Z","title":"Contrastive Learning and Adversarial Disentanglement for Privacy-Aware Task-Oriented Semantic Communication","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.22784","snapshot_observed_at":"2026-08-04T18:26:54.990546Z","title":"Contrastive learning and adversar- ial disentanglement for task-oriented semantic communications,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.09955","last_updated":"2025-09-12T04:11:59Z","snapshot_observed_at":"2026-08-10T02:33:40.494136Z","submitted_at":"2025-09-12T04:11:59Z","title":"Adaptive Token Merging for Efficient Transformer Semantic Communication at the Edge","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-04T18:26:54.990546Z"},"links":{"cited_paper":"/paper/2410.22784","citing_paper":"/paper/2509.09955"},"observation_digest":"sha256:c47b1026b5ebe05a46dab769e918e7902538cff548d74c26b1c62a7b08873980","observation_id":"481cbdc2-6432-444a-a7fe-fd297cb0b431","resolution":{"observed_at":"2026-08-04T18:26:54.990546Z","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":"2026-08-04T18:26:54.994959Z","title":"Attention is all you need,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2509.09955","last_updated":"2025-09-12T04:11:59Z","snapshot_observed_at":"2026-08-10T02:33:40.494136Z","submitted_at":"2025-09-12T04:11:59Z","title":"Adaptive Token Merging for Efficient Transformer Semantic Communication at the Edge","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-04T18:26:54.994959Z"},"links":{"citing_paper":"/paper/2509.09955"},"observation_digest":"sha256:c3c1c1fd870b7d1fadcd236d27df33121e15ccdabb6f3c0cec380f37f01efdf0","observation_id":"fb5ecf59-cff7-4ca1-8a10-2a93ba50ae33","resolution":{"observed_at":"2026-08-04T18:26:54.994959Z","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":"2026-08-04T18:26:54.998819Z","title":"A comprehensive overview of large language models,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.09955","last_updated":"2025-09-12T04:11:59Z","snapshot_observed_at":"2026-08-10T02:33:40.494136Z","submitted_at":"2025-09-12T04:11:59Z","title":"Adaptive Token Merging for Efficient Transformer Semantic Communication at the Edge","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-04T18:26:54.998819Z"},"links":{"citing_paper":"/paper/2509.09955"},"observation_digest":"sha256:9cba6a479d4a61cdd2ae523e9507c0b0fe7d7a1939cb9f59b1b82d9b36dce2a3","observation_id":"70d9f26d-b0ba-4d65-baf2-ea585409e6dd","resolution":{"observed_at":"2026-08-04T18:26:54.998819Z","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":"2026-08-04T18:26:55.002853Z","title":"Large multi-modal models (lmms) as universal foundation models for ai-native wireless systems,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.09955","last_updated":"2025-09-12T04:11:59Z","snapshot_observed_at":"2026-08-10T02:33:40.494136Z","submitted_at":"2025-09-12T04:11:59Z","title":"Adaptive Token Merging for Efficient Transformer Semantic Communication at the Edge","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-04T18:26:55.002853Z"},"links":{"citing_paper":"/paper/2509.09955"},"observation_digest":"sha256:ff94f7d217b638fd861c855c01d93004e0e2808721d421fd2442e9adab5967c8","observation_id":"06972eeb-ca06-4ff8-96a4-ba832d9aa2d7","resolution":{"observed_at":"2026-08-04T18:26:55.002853Z","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":"2026-08-04T18:26:55.006684Z","title":"Vqa: Visual question answering,","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2509.09955","last_updated":"2025-09-12T04:11:59Z","snapshot_observed_at":"2026-08-10T02:33:40.494136Z","submitted_at":"2025-09-12T04:11:59Z","title":"Adaptive Token Merging for Efficient Transformer Semantic Communication at the Edge","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-04T18:26:55.006684Z"},"links":{"citing_paper":"/paper/2509.09955"},"observation_digest":"sha256:6c66636a39ee315b589a093210e9ae8bc27bb0034aef315e677b61cceb6bd9fa","observation_id":"bf60784f-3e8e-4f06-893b-f6818d7f90ab","resolution":{"observed_at":"2026-08-04T18:26:55.006684Z","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":"2026-08-04T18:26:55.010664Z","title":"A compre- hensive survey of deep learning for image captioning,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2509.09955","last_updated":"2025-09-12T04:11:59Z","snapshot_observed_at":"2026-08-10T02:33:40.494136Z","submitted_at":"2025-09-12T04:11:59Z","title":"Adaptive Token Merging for Efficient Transformer Semantic Communication at the Edge","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-04T18:26:55.010664Z"},"links":{"citing_paper":"/paper/2509.09955"},"observation_digest":"sha256:98269b93ef03330315441296533ec8920a68e078f0ad6b4cc34738d498ca10c3","observation_id":"8e902951-6ffc-4d99-bde6-8b6eb5c10277","resolution":{"observed_at":"2026-08-04T18:26:55.010664Z","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":"2026-08-04T18:26:55.014717Z","title":"Blip: Bootstrapping language-image pre-training for unified vision-language understanding and generation,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2509.09955","last_updated":"2025-09-12T04:11:59Z","snapshot_observed_at":"2026-08-10T02:33:40.494136Z","submitted_at":"2025-09-12T04:11:59Z","title":"Adaptive Token Merging for Efficient Transformer Semantic Communication at the Edge","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-04T18:26:55.014717Z"},"links":{"citing_paper":"/paper/2509.09955"},"observation_digest":"sha256:45ef4bbb62b1e76ff37c8e670aae714ec3d83a657ac7f08c8009d69633cc727a","observation_id":"9f796dd9-6554-413e-af51-b2670037d41e","resolution":{"observed_at":"2026-08-04T18:26:55.014717Z","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":"2026-08-04T18:26:55.018444Z","title":"Visual instruction tuning,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.09955","last_updated":"2025-09-12T04:11:59Z","snapshot_observed_at":"2026-08-10T02:33:40.494136Z","submitted_at":"2025-09-12T04:11:59Z","title":"Adaptive Token Merging for Efficient Transformer Semantic Communication at the Edge","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-04T18:26:55.018444Z"},"links":{"citing_paper":"/paper/2509.09955"},"observation_digest":"sha256:6936bcee9d787f89f5ac0f6e0b76572f3363422e64ed7955ccf40a4e8e695c5a","observation_id":"8837d455-0c23-4d78-b6db-4816dd1c8fad","resolution":{"observed_at":"2026-08-04T18:26:55.018444Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.08774","last_updated":"2024-03-04T06:01:33Z","snapshot_observed_at":"2026-08-17T09:58:46.058102Z","submitted_at":"2023-03-15T17:15:04Z","title":"GPT-4 Technical Report","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.08774","snapshot_observed_at":"2026-08-04T18:26:55.022155Z","title":"Gpt-4 technical report,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.09955","last_updated":"2025-09-12T04:11:59Z","snapshot_observed_at":"2026-08-10T02:33:40.494136Z","submitted_at":"2025-09-12T04:11:59Z","title":"Adaptive Token Merging for Efficient Transformer Semantic Communication at the Edge","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-04T18:26:55.022155Z"},"links":{"cited_paper":"/paper/2303.08774","citing_paper":"/paper/2509.09955"},"observation_digest":"sha256:5129e3c81bc1d4f4a9c3fc2378fcefd90b1f7433bc0240a4e716514f61526d73","observation_id":"2be4f92d-6463-4741-8798-d21e394be856","resolution":{"observed_at":"2026-08-04T18:26:55.022155Z","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":"2026-08-04T18:26:55.026154Z","title":"Edge artificial intelligence for 6g: Vision, enabling technologies, and applications,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2509.09955","last_updated":"2025-09-12T04:11:59Z","snapshot_observed_at":"2026-08-10T02:33:40.494136Z","submitted_at":"2025-09-12T04:11:59Z","title":"Adaptive Token Merging for Efficient Transformer Semantic Communication at the Edge","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-04T18:26:55.026154Z"},"links":{"citing_paper":"/paper/2509.09955"},"observation_digest":"sha256:a928da5db187ca1c9a8947bcb7785db218c48657b9f8d5bb391ef902c46c1523","observation_id":"c0926de7-720c-491c-8c17-0b7323666c40","resolution":{"observed_at":"2026-08-04T18:26:55.026154Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1807.02811","last_updated":"2018-07-08T13:06:26Z","snapshot_observed_at":"2026-08-18T00:58:48.914606Z","submitted_at":"2018-07-08T13:06:26Z","title":"A Tutorial on Bayesian Optimization","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1807.02811","snapshot_observed_at":"2026-08-04T18:26:55.029926Z","title":"A tutorial on bayesian optimization,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2509.09955","last_updated":"2025-09-12T04:11:59Z","snapshot_observed_at":"2026-08-10T02:33:40.494136Z","submitted_at":"2025-09-12T04:11:59Z","title":"Adaptive Token Merging for Efficient Transformer Semantic Communication at the Edge","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-04T18:26:55.029926Z"},"links":{"cited_paper":"/paper/1807.02811","citing_paper":"/paper/2509.09955"},"observation_digest":"sha256:ae6940d1892b69a7a7a8ff1bd62ae82d976be25c218e2932e13fb76c3e6952a7","observation_id":"f9e70f94-7a2b-4fe1-868f-e08fa9e2988f","resolution":{"observed_at":"2026-08-04T18:26:55.029926Z","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":"2026-08-04T18:26:55.033958Z","title":"Model inversion attacks that exploit confidence information and basic countermeasures,","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2509.09955","last_updated":"2025-09-12T04:11:59Z","snapshot_observed_at":"2026-08-10T02:33:40.494136Z","submitted_at":"2025-09-12T04:11:59Z","title":"Adaptive Token Merging for Efficient Transformer Semantic Communication at the Edge","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-04T18:26:55.033958Z"},"links":{"citing_paper":"/paper/2509.09955"},"observation_digest":"sha256:efd68a439aefd0f88d5c87eacd76b57801668c0f0d8a3bd4ddcc0e75f82deff0","observation_id":"81ec7e98-d851-438b-855e-536740e16fd5","resolution":{"observed_at":"2026-08-04T18:26:55.033958Z","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":"2026-08-04T18:26:55.037664Z","title":"Edge ai: On-demand acceler- ating deep neural network inference via edge computing,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2509.09955","last_updated":"2025-09-12T04:11:59Z","snapshot_observed_at":"2026-08-10T02:33:40.494136Z","submitted_at":"2025-09-12T04:11:59Z","title":"Adaptive Token Merging for Efficient Transformer Semantic Communication at the Edge","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-04T18:26:55.037664Z"},"links":{"citing_paper":"/paper/2509.09955"},"observation_digest":"sha256:c3a32efc2922de292e58ece41066cc03859157a5d6dc9ed2b59c412918c08046","observation_id":"3f76b3e2-f246-46fd-8b2d-73ce5006c2c2","resolution":{"observed_at":"2026-08-04T18:26:55.037664Z","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":"2026-08-04T18:26:55.042248Z","title":"Energy-aware inference offloading for dnn-driven applications in mobile edge clouds,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2509.09955","last_updated":"2025-09-12T04:11:59Z","snapshot_observed_at":"2026-08-10T02:33:40.494136Z","submitted_at":"2025-09-12T04:11:59Z","title":"Adaptive Token Merging for Efficient Transformer Semantic Communication at the Edge","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-04T18:26:55.042248Z"},"links":{"citing_paper":"/paper/2509.09955"},"observation_digest":"sha256:bdea89998242e1397e14b23ce4f80dda766d05d0e5952feb99ca2a5f6795a793","observation_id":"dc7740ad-ab8d-4f10-a00c-00411f35938d","resolution":{"observed_at":"2026-08-04T18:26:55.042248Z","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":"2026-08-04T18:26:55.046316Z","title":"Partial offloading scheduling and power allocation for mobile edge computing systems,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2509.09955","last_updated":"2025-09-12T04:11:59Z","snapshot_observed_at":"2026-08-10T02:33:40.494136Z","submitted_at":"2025-09-12T04:11:59Z","title":"Adaptive Token Merging for Efficient Transformer Semantic Communication at the Edge","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-04T18:26:55.046316Z"},"links":{"citing_paper":"/paper/2509.09955"},"observation_digest":"sha256:1e06f8bb6e528c70f38965495a27b08a945be33b04c2bf1a87a116b39218629b","observation_id":"a99302cb-62d8-431b-a548-379b6f3dbe12","resolution":{"observed_at":"2026-08-04T18:26:55.046316Z","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":"2026-08-04T18:26:55.050629Z","title":"Swinjscc: Taming swin transformer for deep joint source-channel coding,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.09955","last_updated":"2025-09-12T04:11:59Z","snapshot_observed_at":"2026-08-10T02:33:40.494136Z","submitted_at":"2025-09-12T04:11:59Z","title":"Adaptive Token Merging for Efficient Transformer Semantic Communication at the Edge","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-04T18:26:55.050629Z"},"links":{"citing_paper":"/paper/2509.09955"},"observation_digest":"sha256:d4960358a15c42b39f58bc197f23383b5e13a788e33bb248aa0027911bab96fc","observation_id":"2903b4ac-f2fb-434e-b0db-0baacc63c52c","resolution":{"observed_at":"2026-08-04T18:26:55.050629Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.12096","last_updated":"2026-07-03T18:33:04Z","snapshot_observed_at":"2026-08-18T12:57:16.870530Z","submitted_at":"2025-02-17T18:14:18Z","title":"Token Communications: A Large Model-Driven Framework for Cross-modal Context-aware Semantic Communications","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.12096","snapshot_observed_at":"2026-08-04T18:26:55.054983Z","title":"Token communications: A unified framework for cross-modal context-aware semantic communications,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2509.09955","last_updated":"2025-09-12T04:11:59Z","snapshot_observed_at":"2026-08-10T02:33:40.494136Z","submitted_at":"2025-09-12T04:11:59Z","title":"Adaptive Token Merging for Efficient Transformer Semantic Communication at the Edge","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-04T18:26:55.054983Z"},"links":{"cited_paper":"/paper/2502.12096","citing_paper":"/paper/2509.09955"},"observation_digest":"sha256:4bd0b2c310b52fba7fd56d41f5251903d060416969fee069f8335909dd2f52f1","observation_id":"391a34c2-e181-472f-940d-47eaa1514809","resolution":{"observed_at":"2026-08-04T18:26:55.054983Z","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":"2026-08-04T18:26:55.059414Z","title":"Toward intelligent communications: Large model empowered semantic communications,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2509.09955","last_updated":"2025-09-12T04:11:59Z","snapshot_observed_at":"2026-08-10T02:33:40.494136Z","submitted_at":"2025-09-12T04:11:59Z","title":"Adaptive Token Merging for Efficient Transformer Semantic Communication at the Edge","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-04T18:26:55.059414Z"},"links":{"citing_paper":"/paper/2509.09955"},"observation_digest":"sha256:3f7f25e9ab3b613e9f976172c239b5cf6295e1702af35cfcaf17669463dcb475","observation_id":"5fa37ed2-e45b-411a-aaec-319f84ceccce","resolution":{"observed_at":"2026-08-04T18:26:55.059414Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.02330","last_updated":"2024-04-25T13:49:50Z","snapshot_observed_at":"2026-08-18T07:40:30.031062Z","submitted_at":"2024-04-25T13:49:50Z","title":"Adaptive Semantic Token Selection for AI-native Goal-oriented Communications","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.02330","snapshot_observed_at":"2026-08-04T18:26:55.063401Z","title":"Adaptive semantic token selection for ai-native goal-oriented commu- nications,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.09955","last_updated":"2025-09-12T04:11:59Z","snapshot_observed_at":"2026-08-10T02:33:40.494136Z","submitted_at":"2025-09-12T04:11:59Z","title":"Adaptive Token Merging for Efficient Transformer Semantic Communication at the Edge","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-04T18:26:55.063401Z"},"links":{"cited_paper":"/paper/2405.02330","citing_paper":"/paper/2509.09955"},"observation_digest":"sha256:f6fd8bed79fbc08994f50c56229426069d1e4faf563b551628d8ceb83a316f42","observation_id":"b8d5fbe3-7456-47f6-8766-93c95e6f79f1","resolution":{"observed_at":"2026-08-04T18:26:55.063401Z","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":"2026-08-04T18:26:55.067612Z","title":"Token merging: Your vit but faster,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.09955","last_updated":"2025-09-12T04:11:59Z","snapshot_observed_at":"2026-08-10T02:33:40.494136Z","submitted_at":"2025-09-12T04:11:59Z","title":"Adaptive Token Merging for Efficient Transformer Semantic Communication at the Edge","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-04T18:26:55.067612Z"},"links":{"citing_paper":"/paper/2509.09955"},"observation_digest":"sha256:83a7b23be82b36e88b33c6eb0fe9ce705aea41b526800e96e242ad9c42edc74d","observation_id":"5cbec1e3-5f98-4d16-b08c-664dc1959318","resolution":{"observed_at":"2026-08-04T18:26:55.067612Z","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":"2026-08-04T18:26:55.071595Z","title":"Adaptive sparse vit: towards learnable adaptive token pruning by fully exploiting self-attention,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.09955","last_updated":"2025-09-12T04:11:59Z","snapshot_observed_at":"2026-08-10T02:33:40.494136Z","submitted_at":"2025-09-12T04:11:59Z","title":"Adaptive Token Merging for Efficient Transformer Semantic Communication at the Edge","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-04T18:26:55.071595Z"},"links":{"citing_paper":"/paper/2509.09955"},"observation_digest":"sha256:e19453d9f09760d6f1f490cb807ded21f4c0b53e1c1381dd33a973294c5d462a","observation_id":"ce9e014b-f888-447e-a67d-1c0268d2dd61","resolution":{"observed_at":"2026-08-04T18:26:55.071595Z","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":"2026-08-04T18:26:55.075776Z","title":"Token fusion: Bridging the gap between token pruning and token merging,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.09955","last_updated":"2025-09-12T04:11:59Z","snapshot_observed_at":"2026-08-10T02:33:40.494136Z","submitted_at":"2025-09-12T04:11:59Z","title":"Adaptive Token Merging for Efficient Transformer Semantic Communication at the Edge","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-04T18:26:55.075776Z"},"links":{"citing_paper":"/paper/2509.09955"},"observation_digest":"sha256:1bb0bd6ed79ae579bcd2dc48a7146f78ca586ecf439128825f91eaa3c33281bd","observation_id":"05e7da4c-85ce-4d39-bc0b-62b07eb19113","resolution":{"observed_at":"2026-08-04T18:26:55.075776Z","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":"2026-08-04T18:26:55.080002Z","title":"An image is worth 1/2 tokens after layer 2: Plug-and-play inference acceleration for large vision-language models,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.09955","last_updated":"2025-09-12T04:11:59Z","snapshot_observed_at":"2026-08-10T02:33:40.494136Z","submitted_at":"2025-09-12T04:11:59Z","title":"Adaptive Token Merging for Efficient Transformer Semantic Communication at the Edge","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-04T18:26:55.080002Z"},"links":{"citing_paper":"/paper/2509.09955"},"observation_digest":"sha256:4eed79407b6d7fb11d1f4587a7f20c156c732444b8c247d71de73ae34aa78641","observation_id":"d0157331-70a5-455c-b0f0-a76c7a8d161d","resolution":{"observed_at":"2026-08-04T18:26:55.080002Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.04417","last_updated":"2025-06-03T04:12:10Z","snapshot_observed_at":"2026-08-15T01:31:24.363496Z","submitted_at":"2024-10-06T09:18:04Z","title":"SparseVLM: Visual Token Sparsification for Efficient Vision-Language Model Inference","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.04417","snapshot_observed_at":"2026-08-04T18:26:55.083957Z","title":"Sparsevlm: Visual token sparsification for efficient vision-language model inference,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.09955","last_updated":"2025-09-12T04:11:59Z","snapshot_observed_at":"2026-08-10T02:33:40.494136Z","submitted_at":"2025-09-12T04:11:59Z","title":"Adaptive Token Merging for Efficient Transformer Semantic Communication at the Edge","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-04T18:26:55.083957Z"},"links":{"cited_paper":"/paper/2410.04417","citing_paper":"/paper/2509.09955"},"observation_digest":"sha256:4ab648d5d9bcb0f9999cff3e785ebb607169fd0b68175f754ede597027e534c6","observation_id":"d3ffd459-c0a8-4ae1-9314-4b28c2d20b69","resolution":{"observed_at":"2026-08-04T18:26:55.083957Z","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":"2026-08-04T18:26:55.088193Z","title":"Fit and prune: Fast and training- free visual token pruning for multi-modal large language models,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2509.09955","last_updated":"2025-09-12T04:11:59Z","snapshot_observed_at":"2026-08-10T02:33:40.494136Z","submitted_at":"2025-09-12T04:11:59Z","title":"Adaptive Token Merging for Efficient Transformer Semantic Communication at the Edge","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-04T18:26:55.088193Z"},"links":{"citing_paper":"/paper/2509.09955"},"observation_digest":"sha256:e9296bfbb9dfebb750787d4306faeb1c91b3cf5c3b06c6f8b50f59f248a2ea87","observation_id":"73ebca85-8d4f-4e41-b7a2-ed2bdc893d93","resolution":{"observed_at":"2026-08-04T18:26:55.088193Z","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":"2026-08-04T18:26:55.092339Z","title":"Latency-aware neural architecture search with multi-objective bayesian optimization,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2509.09955","last_updated":"2025-09-12T04:11:59Z","snapshot_observed_at":"2026-08-10T02:33:40.494136Z","submitted_at":"2025-09-12T04:11:59Z","title":"Adaptive Token Merging for Efficient Transformer Semantic Communication at the Edge","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-04T18:26:55.092339Z"},"links":{"citing_paper":"/paper/2509.09955"},"observation_digest":"sha256:b385b7904ffa2b83fdfada499d965bc39dbcfbee5591071a53a94c407f0c407f","observation_id":"5e863751-ef3c-4a22-a7fd-ed6c37d212e2","resolution":{"observed_at":"2026-08-04T18:26:55.092339Z","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":"2026-08-04T18:26:55.096963Z","title":"Adversarial examples: Attacks and defenses for deep learning,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2509.09955","last_updated":"2025-09-12T04:11:59Z","snapshot_observed_at":"2026-08-10T02:33:40.494136Z","submitted_at":"2025-09-12T04:11:59Z","title":"Adaptive Token Merging for Efficient Transformer Semantic Communication at the Edge","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-04T18:26:55.096963Z"},"links":{"citing_paper":"/paper/2509.09955"},"observation_digest":"sha256:facd77bc7ff15ac6e1279fa8cbb70f3b460a7b65b80b8a3ff019a65a06d8f450","observation_id":"0171b01f-02c4-48e7-b190-15b3e81da84e","resolution":{"observed_at":"2026-08-04T18:26:55.096963Z","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":"2026-08-04T18:26:55.102506Z","title":"Advflow: Incon- spicuous black-box adversarial attacks using normalizing flows,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2509.09955","last_updated":"2025-09-12T04:11:59Z","snapshot_observed_at":"2026-08-10T02:33:40.494136Z","submitted_at":"2025-09-12T04:11:59Z","title":"Adaptive Token Merging for Efficient Transformer Semantic Communication at the Edge","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-04T18:26:55.102506Z"},"links":{"citing_paper":"/paper/2509.09955"},"observation_digest":"sha256:dbf04a3afc98579f1d021e52f7929899fd31e801440ec971fca630d4b9e6ceba","observation_id":"ba6a18b1-7891-43a1-b41a-c7675e264911","resolution":{"observed_at":"2026-08-04T18:26:55.102506Z","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":"2026-08-04T18:26:55.106405Z","title":"On the computational complexity of self-attention,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.09955","last_updated":"2025-09-12T04:11:59Z","snapshot_observed_at":"2026-08-10T02:33:40.494136Z","submitted_at":"2025-09-12T04:11:59Z","title":"Adaptive Token Merging for Efficient Transformer Semantic Communication at the Edge","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-04T18:26:55.106405Z"},"links":{"citing_paper":"/paper/2509.09955"},"observation_digest":"sha256:dcbb2a86445a996abba9ca27808f07723e06cce290076e6ea20836e791e840de","observation_id":"106ec965-75ce-4f17-9fd1-25f6559081b1","resolution":{"observed_at":"2026-08-04T18:26:55.106405Z","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":"2026-08-04T18:26:55.110687Z","title":"A bayesian approach to constrained single-and multi-objective optimization,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2509.09955","last_updated":"2025-09-12T04:11:59Z","snapshot_observed_at":"2026-08-10T02:33:40.494136Z","submitted_at":"2025-09-12T04:11:59Z","title":"Adaptive Token Merging for Efficient Transformer Semantic Communication at the Edge","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-04T18:26:55.110687Z"},"links":{"citing_paper":"/paper/2509.09955"},"observation_digest":"sha256:959458e286f716fac45e21097101c73b33e1e6c3a406d1bd79659e8eaf1d8b0a","observation_id":"225c7110-b424-4992-8f0e-160d4e1e66b2","resolution":{"observed_at":"2026-08-04T18:26:55.110687Z","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":"2026-08-04T18:26:55.114640Z","title":"Classes of kernels for machine learning: a statistics perspective,","venue":null,"work_id":null,"year":2001},"citing_paper":{"arxiv_id":"2509.09955","last_updated":"2025-09-12T04:11:59Z","snapshot_observed_at":"2026-08-10T02:33:40.494136Z","submitted_at":"2025-09-12T04:11:59Z","title":"Adaptive Token Merging for Efficient Transformer Semantic Communication at the Edge","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-04T18:26:55.114640Z"},"links":{"citing_paper":"/paper/2509.09955"},"observation_digest":"sha256:eaeb6021fc2566162616a9477f7173096eb9086c909fbb522b74e29342fe029e","observation_id":"416673f3-f706-44f9-9a52-527a8c97cfbb","resolution":{"observed_at":"2026-08-04T18:26:55.114640Z","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":"2026-08-04T18:26:55.118674Z","title":"Gaussian processes in machine learning,","venue":null,"work_id":null,"year":2003},"citing_paper":{"arxiv_id":"2509.09955","last_updated":"2025-09-12T04:11:59Z","snapshot_observed_at":"2026-08-10T02:33:40.494136Z","submitted_at":"2025-09-12T04:11:59Z","title":"Adaptive Token Merging for Efficient Transformer Semantic Communication at the Edge","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-04T18:26:55.118674Z"},"links":{"citing_paper":"/paper/2509.09955"},"observation_digest":"sha256:15ecf91ad923000b055f88db8b9cf47cf5d85b90cf039b9c91666338ff4458d9","observation_id":"cd598053-0e0b-4c2f-bb96-1f15280c95c9","resolution":{"observed_at":"2026-08-04T18:26:55.118674Z","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":"2026-08-04T18:26:55.122599Z","title":"Multi-objective optimisation using evolutionary algorithms: an introduction,","venue":null,"work_id":null,"year":2011},"citing_paper":{"arxiv_id":"2509.09955","last_updated":"2025-09-12T04:11:59Z","snapshot_observed_at":"2026-08-10T02:33:40.494136Z","submitted_at":"2025-09-12T04:11:59Z","title":"Adaptive Token Merging for Efficient Transformer Semantic Communication at the Edge","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-04T18:26:55.122599Z"},"links":{"citing_paper":"/paper/2509.09955"},"observation_digest":"sha256:923e1164522cf20c242cfd51c43d5301bcbe14e4f4e939994ca0c38235fa2841","observation_id":"7da515dd-c038-47d3-b416-5a4a4129b071","resolution":{"observed_at":"2026-08-04T18:26:55.122599Z","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":"2026-08-04T18:26:55.126672Z","title":"Multiobjective evolutionary algorithms: a comparative case study and the strength pareto approach,","venue":null,"work_id":null,"year":2002},"citing_paper":{"arxiv_id":"2509.09955","last_updated":"2025-09-12T04:11:59Z","snapshot_observed_at":"2026-08-10T02:33:40.494136Z","submitted_at":"2025-09-12T04:11:59Z","title":"Adaptive Token Merging for Efficient Transformer Semantic Communication at the Edge","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-04T18:26:55.126672Z"},"links":{"citing_paper":"/paper/2509.09955"},"observation_digest":"sha256:0b3e73b4dcfec8ead3991b6a2b13382c20fb04d4299610785fd12785d8ee9a5a","observation_id":"060705f0-02a4-4266-80b5-13d50b507345","resolution":{"observed_at":"2026-08-04T18:26:55.126672Z","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":"2026-08-04T18:26:55.130256Z","title":"Multi-objective bayesian global optimization using expected hypervolume improvement gradient,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2509.09955","last_updated":"2025-09-12T04:11:59Z","snapshot_observed_at":"2026-08-10T02:33:40.494136Z","submitted_at":"2025-09-12T04:11:59Z","title":"Adaptive Token Merging for Efficient Transformer Semantic Communication at the Edge","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-04T18:26:55.130256Z"},"links":{"citing_paper":"/paper/2509.09955"},"observation_digest":"sha256:0b2979ffa5d7011381c83d35d8855389f99b8d7686027894aee242230561808b","observation_id":"164a0c66-5600-4ae9-80ec-ed4083848428","resolution":{"observed_at":"2026-08-04T18:26:55.130256Z","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":"2026-08-04T18:26:55.134164Z","title":"User preferences in bayesian multi- objective optimization: the expected weighted hypervolume improve- ment criterion,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2509.09955","last_updated":"2025-09-12T04:11:59Z","snapshot_observed_at":"2026-08-10T02:33:40.494136Z","submitted_at":"2025-09-12T04:11:59Z","title":"Adaptive Token Merging for Efficient Transformer Semantic Communication at the Edge","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-04T18:26:55.134164Z"},"links":{"citing_paper":"/paper/2509.09955"},"observation_digest":"sha256:0b6528b8210239b1a15bb6cfc6fd6464e17c43e3d3e855777db8cefa60db201f","observation_id":"b6a0ed1f-056a-4e04-a363-34fd8a267437","resolution":{"observed_at":"2026-08-04T18:26:55.134164Z","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":"2026-08-04T18:26:55.137910Z","title":"Differentiable expected hyper- volume improvement for parallel multi-objective bayesian optimization,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2509.09955","last_updated":"2025-09-12T04:11:59Z","snapshot_observed_at":"2026-08-10T02:33:40.494136Z","submitted_at":"2025-09-12T04:11:59Z","title":"Adaptive Token Merging for Efficient Transformer Semantic Communication at the Edge","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-04T18:26:55.137910Z"},"links":{"citing_paper":"/paper/2509.09955"},"observation_digest":"sha256:376fa7aa726dcafbf8be08edb88428b1dc6f16b1647624c85ac20baac5fc19f5","observation_id":"fe01a503-0d31-45da-ae84-f7aa022ca967","resolution":{"observed_at":"2026-08-04T18:26:55.137910Z","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":"2026-08-04T18:26:55.142021Z","title":"Single-and multiobjective evolutionary optimization assisted by gaussian random field metamodels,","venue":null,"work_id":null,"year":2006},"citing_paper":{"arxiv_id":"2509.09955","last_updated":"2025-09-12T04:11:59Z","snapshot_observed_at":"2026-08-10T02:33:40.494136Z","submitted_at":"2025-09-12T04:11:59Z","title":"Adaptive Token Merging for Efficient Transformer Semantic Communication at the Edge","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-04T18:26:55.142021Z"},"links":{"citing_paper":"/paper/2509.09955"},"observation_digest":"sha256:b7017514b838815dfe3d115082446d53a6c3e44eee7a56c079e67d26ff3172b7","observation_id":"d3c824af-cfca-43b4-af18-d18764725115","resolution":{"observed_at":"2026-08-04T18:26:55.142021Z","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":"2026-08-04T18:26:55.146053Z","title":"Masked autoencoders are scalable vision learners,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2509.09955","last_updated":"2025-09-12T04:11:59Z","snapshot_observed_at":"2026-08-10T02:33:40.494136Z","submitted_at":"2025-09-12T04:11:59Z","title":"Adaptive Token Merging for Efficient Transformer Semantic Communication at the Edge","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-04T18:26:55.146053Z"},"links":{"citing_paper":"/paper/2509.09955"},"observation_digest":"sha256:04eb16065046e9a407288490bc1141cb7bfb3238f78f6ded6b667b68e7227af4","observation_id":"0ee61b39-9982-45ac-8601-c080fc383d5a","resolution":{"observed_at":"2026-08-04T18:26:55.146053Z","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":"2026-08-04T18:26:55.149848Z","title":"Learning transferable visual models from natural language supervision,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2509.09955","last_updated":"2025-09-12T04:11:59Z","snapshot_observed_at":"2026-08-10T02:33:40.494136Z","submitted_at":"2025-09-12T04:11:59Z","title":"Adaptive Token Merging for Efficient Transformer Semantic Communication at the Edge","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-04T18:26:55.149848Z"},"links":{"citing_paper":"/paper/2509.09955"},"observation_digest":"sha256:920da053e1f7ca8da594a76d0c85e6acd1e077e4c7acf99fe8ecd2f35d05aa06","observation_id":"ee588ff2-68e1-4f97-bcae-bc0e7f7414d1","resolution":{"observed_at":"2026-08-04T18:26:55.149848Z","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":"2026-08-04T18:26:55.153575Z","title":"Distribution of points in a cube and approximate evaluation of integrals,","venue":null,"work_id":null,"year":1967},"citing_paper":{"arxiv_id":"2509.09955","last_updated":"2025-09-12T04:11:59Z","snapshot_observed_at":"2026-08-10T02:33:40.494136Z","submitted_at":"2025-09-12T04:11:59Z","title":"Adaptive Token Merging for Efficient Transformer Semantic Communication at the Edge","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-04T18:26:55.153575Z"},"links":{"citing_paper":"/paper/2509.09955"},"observation_digest":"sha256:1ca8c21e46f8e36d65efec00e66b002bba292cd2e04e42dabc05afc1cc72e59c","observation_id":"5480f16a-4b33-470a-b37c-1274e0c10ea9","resolution":{"observed_at":"2026-08-04T18:26:55.153575Z","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":"2026-08-04T18:26:55.157293Z","title":"Imagenet: A large-scale hierarchical image database,","venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"2509.09955","last_updated":"2025-09-12T04:11:59Z","snapshot_observed_at":"2026-08-10T02:33:40.494136Z","submitted_at":"2025-09-12T04:11:59Z","title":"Adaptive Token Merging for Efficient Transformer Semantic Communication at the Edge","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-04T18:26:55.157293Z"},"links":{"citing_paper":"/paper/2509.09955"},"observation_digest":"sha256:08b2c514409381c817df32de09ae42411864bc2a24fc4d1b989f305205497223","observation_id":"e6860066-013d-4e04-ae6f-da9810e33dfe","resolution":{"observed_at":"2026-08-04T18:26:55.157293Z","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":"2026-08-04T18:26:55.161235Z","title":"Gqa: A new dataset for real- world visual reasoning and compositional question answering,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2509.09955","last_updated":"2025-09-12T04:11:59Z","snapshot_observed_at":"2026-08-10T02:33:40.494136Z","submitted_at":"2025-09-12T04:11:59Z","title":"Adaptive Token Merging for Efficient Transformer Semantic Communication at the Edge","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-04T18:26:55.161235Z"},"links":{"citing_paper":"/paper/2509.09955"},"observation_digest":"sha256:24a9393ef7a89aa9e779b1411eb60addad6b8fae763d504f9bea963607567fa0","observation_id":"f93ac7bc-28e3-4cca-858c-a083444112d2","resolution":{"observed_at":"2026-08-04T18:26:55.161235Z","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":"2026-08-04T18:26:55.165483Z","title":"Learn to explain: Multimodal reasoning via thought chains for science question answering,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2509.09955","last_updated":"2025-09-12T04:11:59Z","snapshot_observed_at":"2026-08-10T02:33:40.494136Z","submitted_at":"2025-09-12T04:11:59Z","title":"Adaptive Token Merging for Efficient Transformer Semantic Communication at the Edge","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-04T18:26:55.165483Z"},"links":{"citing_paper":"/paper/2509.09955"},"observation_digest":"sha256:468196f6b0b03777894eeeb791d2f18d64646814b0966ba2e7e1d13b6f0b1486","observation_id":"6ba1e18c-011e-4198-ad50-a1365fea7f53","resolution":{"observed_at":"2026-08-04T18:26:55.165483Z","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":"2026-08-04T18:26:55.169512Z","title":"Image quality assessment: from error visibility to structural similarity,","venue":null,"work_id":null,"year":2004},"citing_paper":{"arxiv_id":"2509.09955","last_updated":"2025-09-12T04:11:59Z","snapshot_observed_at":"2026-08-10T02:33:40.494136Z","submitted_at":"2025-09-12T04:11:59Z","title":"Adaptive Token Merging for Efficient Transformer Semantic Communication at the Edge","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-04T18:26:55.169512Z"},"links":{"citing_paper":"/paper/2509.09955"},"observation_digest":"sha256:f32d97b7ccf2245e9e6694cd656144bbb8293cfe03931a8e05e8e556a8a8a211","observation_id":"92a1b55c-484d-44dc-a888-1868be00e2bd","resolution":{"observed_at":"2026-08-04T18:26:55.169512Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2509.09955","last_updated":"2025-09-12T04:11:59Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-10T02:33:40.494136Z","submitted_at":"2025-09-12T04:11:59Z","title":"Adaptive Token Merging for Efficient Transformer Semantic Communication at the Edge"},"reference_resolution":{"displayed":52,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":52,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":52},"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":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"thesis":"As of 18 August 2026, this Paper Citation Record lists 52 of 52 outbound references and 1 inbound Pith citation observation for arXiv:2509.09955."}