{"url":"/dataset/silg","name":"SILG","full_name":"Symbolic Interactive Language Grounding","description_markdown":"**Symbolic Interactive Language Grounding** (**SILG**) is a multi-environment benchmark which unifies a collection of diverse grounded language learning environments under a common interface. SILG consists of grid-world environments that require generalization to new dynamics, entities, and partially observed worlds (RTFM, Messenger, NetHack), as well as symbolic counterparts of visual worlds that require interpreting rich natural language with respect to complex scenes (ALFWorld, Touchdown). Together, these environments provide diverse grounding challenges in richness of observation space, action space, language specification, and plan complexity.","description_withheld":null,"homepage":"https://github.com/vzhong/silg","introduced_date":"2021-10-20","introduced_date_note":null,"introduced_by":{"paper":"/paper/silg-the-multi-environment-symbolic","title":"SILG: The Multi-environment Symbolic Interactive Language Grounding Benchmark","first_author":"Victor Zhong","url":null},"license":{"name":"MIT License","url":"https://github.com/vzhong/silg/blob/main/LICENSE"},"modalities":[{"name":"Environment","url":"/datasets/modality/environment"}],"tasks":[],"languages":[],"variants":["SILG"],"data_loaders":[],"num_papers_in_archive":3,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}