{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/code/truncate-input","entry":"truncate_input","source":"Syntology graph, per-sample; not an archive number","read_at":"2026-09-24T18:15:14+00:00","claim":"Names are grouped by exact entry-name string. Same-named routines are NOT asserted to be equivalent; 'ran' means executed on a synthesized fixture, not correctness. n_samples_ran = sum of by_status over every status except 'unverified' (ran_draft_wrong and ran_fixture are failures of Syntology's instrument, not of the code); n_papers_ran = papers with at least one such sample.","status_vocabulary":{"ran_honours":"ran, honoured the contract we drafted","ran_violates":"ran, violated the contract we drafted","ran_draft_wrong":"ran; our contract draft was wrong, not the code","ran_fixture":"ran; our fixture could not drive it","ran":"ran on a synthesized input","unverified":"unverified (harvested, no recorded run)"},"n_papers":6,"n_papers_ran":6,"units":"n_samples, n_samples_ran, n_samples_fingerprinted and by_status count distinct code bodies (code_sha256); n_places and n_places_pointer_only count places, one per (paper, code body) pair, which is also the unit of the samples list","n_samples":4,"n_samples_ran":4,"n_samples_fingerprinted":4,"n_places":7,"n_places_pointer_only":4,"by_status":{"ran_honours":0,"ran_violates":0,"ran_draft_wrong":0,"ran_fixture":2,"ran":2,"unverified":0},"syntology":{"atlas_url":null,"mcp":null,"mcp_per_sample":{"tool":"get_code","arguments_in":"samples[].mcp_get_code"},"developers":"https://syntology.ai/developers"},"samples":[{"arxiv_id":"2408.11745","paper":"/paper/focusllm-scaling-llm-s-context-by-parallel","title":"FocusLLM: Precise Understanding of Long Context by Dynamic Condensing","date":"2024-08-21","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"leezythu/focusllm","path":"infbench_src/eval_chatglm.py","file_url":"https://github.com/leezythu/focusllm/blob/HEAD/infbench_src/eval_chatglm.py","status":"ran_fixture","verification_level":1,"contract_check":"RAISES","metamorphic_tier":"well_formed","behaviour_fingerprint":true,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"a09f1fe8cdcea888","mcp_get_code":{"code_sha256":"a09f1fe8cdcea888"}},{"arxiv_id":"2407.02490","paper":"/paper/minference-1-0-accelerating-pre-filling-for","title":"MInference 1.0: Accelerating Pre-filling for Long-Context LLMs via Dynamic Sparse Attention","date":"2024-07-02","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"microsoft/MInference","path":"experiments/infinite_bench/run_infinitebench.py","file_url":"https://github.com/microsoft/MInference/blob/HEAD/experiments/infinite_bench/run_infinitebench.py","status":"ran_fixture","verification_level":1,"contract_check":"RAISES","metamorphic_tier":"well_formed","behaviour_fingerprint":true,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"db3017985563c2a7","mcp_get_code":{"code_sha256":"db3017985563c2a7"}},{"arxiv_id":"2402.14154","paper":"/paper/mm-soc-benchmarking-multimodal-large-language","title":"MM-Soc: Benchmarking Multimodal Large Language Models in Social Media Platforms","date":"2024-02-21","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"claws-lab/mmsoc","path":"mmsoc/utils/model_utils.py","file_url":"https://github.com/claws-lab/mmsoc/blob/HEAD/mmsoc/utils/model_utils.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"d146939d9fdf8a96","mcp_get_code":{"code_sha256":"d146939d9fdf8a96"}},{"arxiv_id":"2402.14154","paper":"/paper/mm-soc-benchmarking-multimodal-large-language","title":"MM-Soc: Benchmarking Multimodal Large Language Models in Social Media Platforms","date":"2024-02-21","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"claws-lab/mmsoc","path":"mmsoc/utils/data_utils.py","file_url":"https://github.com/claws-lab/mmsoc/blob/HEAD/mmsoc/utils/data_utils.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"1374fce5cd4d2302","mcp_get_code":{"code_sha256":"1374fce5cd4d2302"}},{"arxiv_id":"2402.13718","paper":"/paper/infty-bench-extending-long-context-evaluation","title":"$\\infty$Bench: Extending Long Context Evaluation Beyond 100K Tokens","date":"2024-02-21","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":null,"path":"","file_url":null,"status":"ran_fixture","verification_level":1,"contract_check":"RAISES","metamorphic_tier":"well_formed","behaviour_fingerprint":true,"licence":null,"inline_ok":false,"code_sha256_prefix":"a09f1fe8cdcea888","mcp_get_code":{"code_sha256":"a09f1fe8cdcea888"}},{"arxiv_id":"2402.10171","paper":"/paper/data-engineering-for-scaling-language-models","title":"Data Engineering for Scaling Language Models to 128K Context","date":"2024-02-15","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"franxyao/long-context-data-engineering","path":"eval/book/eval_book.py","file_url":"https://github.com/franxyao/long-context-data-engineering/blob/HEAD/eval/book/eval_book.py","status":"ran_fixture","verification_level":1,"contract_check":"RAISES","metamorphic_tier":"well_formed","behaviour_fingerprint":true,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"a09f1fe8cdcea888","mcp_get_code":{"code_sha256":"a09f1fe8cdcea888"}},{"arxiv_id":"2025.acl-long.1500","paper":null,"title":"arXiv:2025.acl-long.1500","date":null,"month_inferred_from_arxiv_id":null,"title_source":null,"repo":"leezythu/FocusLLM","path":"infbench_src/eval_chatglm.py","file_url":"https://github.com/leezythu/FocusLLM/blob/HEAD/infbench_src/eval_chatglm.py","status":"ran_fixture","verification_level":1,"contract_check":"RAISES","metamorphic_tier":"well_formed","behaviour_fingerprint":true,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"a09f1fe8cdcea888","mcp_get_code":{"code_sha256":"a09f1fe8cdcea888"}}]}