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We introduce RSAT, a method that trains small language models (SLMs, 1-8B) to produce step-by-step reasoning with cell-level citations grounded in table evidence. Phase 1 (SFT) teaches a structured JSON output format from verified reasoning traces. Phase 2 (GRPO) optimizes a composite reward centered on NLI-based faithfulness, alongside citation validity and parsimony. Across six models from two families-Qwen 2.5 (1.5B/3B/7B) and Llama 3 (1B/3B/8B)-RSAT improves faithfulness 3.7$\\times$ over SFT alone (0.224$\\rightarrow$0.826), with near-perfect citation validity (0.992). Post-hoc attribution collapses below 13% format success, confirming that attribution must be integrated into reasoning, not retrofitted. Ablations show the faithfulness reward is essential: removing it drops faithfulness from 0.97 to 0.03.","title":"RSAT: Structured Attribution Makes Small Language Models Faithful Table Reasoners","url":"https://arxiv.org/abs/2605.00199","vendor":"arxiv_cs_ai"},"summary":"arXiv:2605.00199v1 Announce Type: cross \nAbstract: When a language model answers a table question, users have no way to verify which cells informed which reasoning steps. We introduce RSAT, a method that trains small language models (SLMs, 1-8B) to produce step-by-step reasoning with cell-level citations grounded in table evidence. Phase 1 (SFT) teaches a structured JSON output format from verified reasoning traces. Phase 2 (GRPO) optimizes a composite reward centered on NLI-based faithfulness, alongside citation validity and parsimony. 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Ablations show the faithfulness reward is essential: removing it drops faithfulness from 0.97 to 0.03.","title":"RSAT: Structured Attribution Makes Small Language Models Faithful Table Reasoners","vendor":"arxiv_cs_ai"},"confidence":{"method":"deterministic"},"decision":"POSITIVE","issued_at":"2026-05-05T04:43:28Z","notes":"Spider vendor_press (news) news.vendor_press.v1","object":{"captured_by":"crovia.spider.vendor_press","primary_source_url":"https://arxiv.org/abs/2605.00199"},"predecessors":[],"schema":"crovia.axiom.v1","signature":"ed25519:853571544adc32af8f84415a47e69939230dd747baa711848b42bcd9e4e5055b84931a5169739dcdbce09a85034275ab44efdd0e4c4c80d581bea061bdc8020e","signer":"crovia.substrate","subject":{"observed_at":"2026-05-05T04:43:28Z","source_collector":"spider:vendor_press","target_id":"https://arxiv.org/abs/2605.00199"},"tsa":{"authority":"crovia.substrate.bootstrap","rfc3161_token":"{\"kind\":\"crovia.bootstrap.tsa\",\"source_jsonl\":\"/opt/crovia/spider/data/news/vendor_press_v1.jsonl\",\"source_seal_merkle_root\":\"spider_vendor_press_v1\",\"upgrade_path\":\"Sessione H \\u2014 OpenTimestamps weekly anchor\"}"},"zk_mode":"clear","zk_proof":null},"ledger":{"leaf_hash":"c913165258ef0c2e876041019c96d258433f42cb90c49c74648c663e4c71f7bd","leaf_index":114274,"ledger_path":"/opt/crovia/substrate/axiom_ledger.jsonl"},"merkle_proof":{"hash_alg":"sha256","leaf_prefix":"0x00","node_prefix":"0x01","odd_leaf_rule":"duplicate_last","path":[{"sibling":"5a6cec7f347be0df8bdd1e9b275254a100a6c49e4cfb4706d76b216edf415842","side":"right"},{"sibling":"c9ecd36e738e3ee37cdac3f164b4a3ae052afe3e0208adbe0cda24d79e6a08c3","side":"left"},{"sibling":"73c0ca9d33430149a617ab9a11f0c375ee7c9467d115e24e3ed17edcf3d58895","side":"right"},{"sibling":"cf2da3c1e6fc4eacb93830e9169cd6ae0e3cf2d095bfcd1e8903246190e3168f","side":"right"},{"sibling":"6ba45046af77961de3939d5c39c0492561ede31871b5f9eb901aaa71a1ca9635","side":"right"},{"sibling":"1ad9ec90a9658a83c439eced513cb663f1576046e8ed981a3ed327a1e9106c96","side":"left"},{"sibling":"864ff8c61e24143ac1684572b26ed4ff162b3c2195104f55103383456befd161","side":"left"},{"sibling":"46dca532ded31bba3e38a2fc1bf625ddbe113eaf158d9999dfa7f7d5674bbb32","side":"right"},{"sibling":"17e21f83c86c2a86dddad911d22393ee81f41d8e0b79ef8c0c48668ea846f2ca","side":"right"},{"sibling":"8df6c69f776fbba620634f6baf125eeaa6fdf9426e461e649028010d9a703f42","side":"left"},{"sibling":"ea40d1bd0432ad4dd90f023c692aaab8c8f54e27ce652e82f2ec8e16cacfb632","side":"left"},{"sibling":"673cd6d27b696232f7f65e7a0733c7df6bc9fac3bcb569907ebb0de1c72c4bb2","side":"left"},{"sibling":"76d7c4385d71ae8104107105be66eddb792e01ed6e493db5a9b4eec5441abb76","side":"left"},{"sibling":"b03f005860bf95148ea89c703a32ca19ab7a2ca71b58bb628ff94a9edb8703b0","side":"left"},{"sibling":"21d1e30b556f553dc939fddc23e6367f0a7755ebe3dd489dc0001cef017beb7f","side":"right"},{"sibling":"f2817ab288b5324fe49770372c7a10f33f7cd11005f8d4c0a730316f5229dc98","side":"left"},{"sibling":"725fac972e772ca0dc598810ea1abc70df472f72d2d6ab8a0baee2b80e5d2f4c","side":"left"},{"sibling":"98fc57dfef8873b512edc8340f7181df57302bb96777625e072235c62d7c5895","side":"right"}]},"schema":"crovia.axiom_proof.v1","seal":{"first_collector_run_id":"","first_receipt_hash":"","jsonl_path":"/opt/crovia/substrate/axiom_ledger.jsonl","key_id":"430895f101d38164","last_collector_run_id":"","last_receipt_hash":"","leaf_count":134292,"merkle_root":"77fc9c28fae777b81da5b495b3115474df6592dfac590333213d3bdf8b94a9b3","public_key_hex":"cf742e26f75669dc673cb5c0786a1ae23ae8ca19c347317192ce40c28a7ff25c","run_id":"hourly_json_retrofit_20260515T023701Z","schema":"crovia.seal.v1","seal_family_version":"crovia-seal-family/1","seal_kind":"substrate_batch","sealed_at":"2026-05-15T02:37:25Z","sig_algorithm":"ed25519","signature":"68107a834b00b24f5d4501e5ec727445311f132a486567ecc4c72a4e6dff24c8c21f2de3105293353ba5fdbe370d032819af6aa70f694e2e39b6af6737507009","signer_version":"1.1.0"},"trust_root":{"key_id":"430895f101d38164","public_key_hex":"cf742e26f75669dc673cb5c0786a1ae23ae8ca19c347317192ce40c28a7ff25c","signature_algorithm":"ed25519","url":"/registry/canon/TRUST_ROOT.md"},"verifier":{"spec":"/registry/canon/AXIOM_RECEIPT_v1.md","url":"/v/axm_71fe32f5be66ca025d4a7dd1f3b2d1fea1f40d5da13ba06d59c469347dbe6b98"}}