{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:JBRWY2ADSH47FPZ347OX6EMLHX","short_pith_number":"pith:JBRWY2AD","schema_version":"1.0","canonical_sha256":"48636c680391f9f2bf3be7dd7f118b3dc0370f7bb1af2f8ad0c9d4f38a291854","source":{"kind":"arxiv","id":"2505.15154","version":1},"attestation_state":"computed","paper":{"title":"Prolonged Reasoning Is Not All You Need: Certainty-Based Adaptive Routing for Efficient LLM/MLLM Reasoning","license":"http://creativecommons.org/publicdomain/zero/1.0/","headline":"","cross_cats":["cs.AI","cs.MM"],"primary_cat":"cs.CL","authors_text":"Bin Shan, Can Huang, Guozhi Tang, Haiyang Yu, Han Wang, Hao Feng, Jinghui Lu, Jingqun Tang, Shiwei Ran, Siliang Xu, Siqi Wang, Teng Fu","submitted_at":"2025-05-21T06:20:17Z","abstract_excerpt":"Recent advancements in reasoning have significantly enhanced the capabilities of Large Language Models (LLMs) and Multimodal Large Language Models (MLLMs) across diverse tasks. However, excessive reliance on chain-of-thought (CoT) reasoning can impair model performance and brings unnecessarily lengthened outputs, reducing efficiency. Our work reveals that prolonged reasoning does not universally improve accuracy and even degrade performance on simpler tasks. To address this, we propose Certainty-based Adaptive Reasoning (CAR), a novel framework that dynamically switches between short answers a"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2505.15154","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"cs.CL","submitted_at":"2025-05-21T06:20:17Z","cross_cats_sorted":["cs.AI","cs.MM"],"title_canon_sha256":"49b552ef244aceb39e95acfc79cafaead51028d1f723eb9105d5b58c5d90a81e","abstract_canon_sha256":"73ba634eb15db4967e33b705da21ee3295711adce1da0e57b17c413add3516dc"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:06:41.376650Z","signature_b64":"Xzgb+zDuK33ORR2vMaXJEEaS0xveP/3EQQf+z9hQG2QFyFb8N8PXW7T0xR+hBjoV+6l2MXncMjBZFykFos6YCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"48636c680391f9f2bf3be7dd7f118b3dc0370f7bb1af2f8ad0c9d4f38a291854","last_reissued_at":"2026-07-05T11:06:41.376164Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:06:41.376164Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Prolonged Reasoning Is Not All You Need: Certainty-Based Adaptive Routing for Efficient LLM/MLLM Reasoning","license":"http://creativecommons.org/publicdomain/zero/1.0/","headline":"","cross_cats":["cs.AI","cs.MM"],"primary_cat":"cs.CL","authors_text":"Bin Shan, Can Huang, Guozhi Tang, Haiyang Yu, Han Wang, Hao Feng, Jinghui Lu, Jingqun Tang, Shiwei Ran, Siliang Xu, Siqi Wang, Teng Fu","submitted_at":"2025-05-21T06:20:17Z","abstract_excerpt":"Recent advancements in reasoning have significantly enhanced the capabilities of Large Language Models (LLMs) and Multimodal Large Language Models (MLLMs) across diverse tasks. However, excessive reliance on chain-of-thought (CoT) reasoning can impair model performance and brings unnecessarily lengthened outputs, reducing efficiency. Our work reveals that prolonged reasoning does not universally improve accuracy and even degrade performance on simpler tasks. To address this, we propose Certainty-based Adaptive Reasoning (CAR), a novel framework that dynamically switches between short answers a"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.15154","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2505.15154/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"2505.15154","created_at":"2026-07-05T11:06:41.376225+00:00"},{"alias_kind":"arxiv_version","alias_value":"2505.15154v1","created_at":"2026-07-05T11:06:41.376225+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.15154","created_at":"2026-07-05T11:06:41.376225+00:00"},{"alias_kind":"pith_short_12","alias_value":"JBRWY2ADSH47","created_at":"2026-07-05T11:06:41.376225+00:00"},{"alias_kind":"pith_short_16","alias_value":"JBRWY2ADSH47FPZ3","created_at":"2026-07-05T11:06:41.376225+00:00"},{"alias_kind":"pith_short_8","alias_value":"JBRWY2AD","created_at":"2026-07-05T11:06:41.376225+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":8,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2607.01602","citing_title":"ProWAFT: A ROMA-LPD Instance for Workload-Aware and Dynamic Fault Tolerance in FPGA-Based CNN Accelerators","ref_index":11,"is_internal_anchor":false},{"citing_arxiv_id":"2606.30189","citing_title":"DAIN: Dynamic Agent-Based Interaction Network for Efficient and Collaborative Multimodal Reasoning","ref_index":41,"is_internal_anchor":false},{"citing_arxiv_id":"2605.18173","citing_title":"Do You Need Text Rectification? Soft Attention Mask Embedding for Rectification-Free Scene Text Spotting","ref_index":54,"is_internal_anchor":false},{"citing_arxiv_id":"2605.10195","citing_title":"Breaking the Reward Barrier: Accelerating Tree-of-Thought Reasoning via Speculative Exploration","ref_index":37,"is_internal_anchor":false},{"citing_arxiv_id":"2605.14548","citing_title":"Local Spatiotemporal Convolutional Network for Robust Gait Recognition","ref_index":45,"is_internal_anchor":false},{"citing_arxiv_id":"2604.03339","citing_title":"Hierarchical Awareness Adapters with Hybrid Pyramid Feature Fusion for Dense Depth Prediction","ref_index":37,"is_internal_anchor":false},{"citing_arxiv_id":"2605.10195","citing_title":"Breaking the Reward Barrier: Accelerating Tree-of-Thought Reasoning via Speculative Exploration","ref_index":37,"is_internal_anchor":false},{"citing_arxiv_id":"2604.05546","citing_title":"Efficient Inference for Large Vision-Language Models: Bottlenecks, Techniques, and Prospects","ref_index":6,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/JBRWY2ADSH47FPZ347OX6EMLHX","json":"https://pith.science/pith/JBRWY2ADSH47FPZ347OX6EMLHX.json","graph_json":"https://pith.science/api/pith-number/JBRWY2ADSH47FPZ347OX6EMLHX/graph.json","events_json":"https://pith.science/api/pith-number/JBRWY2ADSH47FPZ347OX6EMLHX/events.json","paper":"https://pith.science/paper/JBRWY2AD"},"agent_actions":{"view_html":"https://pith.science/pith/JBRWY2ADSH47FPZ347OX6EMLHX","download_json":"https://pith.science/pith/JBRWY2ADSH47FPZ347OX6EMLHX.json","view_paper":"https://pith.science/paper/JBRWY2AD","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2505.15154&json=true","fetch_graph":"https://pith.science/api/pith-number/JBRWY2ADSH47FPZ347OX6EMLHX/graph.json","fetch_events":"https://pith.science/api/pith-number/JBRWY2ADSH47FPZ347OX6EMLHX/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/JBRWY2ADSH47FPZ347OX6EMLHX/action/timestamp_anchor","attest_storage":"https://pith.science/pith/JBRWY2ADSH47FPZ347OX6EMLHX/action/storage_attestation","attest_author":"https://pith.science/pith/JBRWY2ADSH47FPZ347OX6EMLHX/action/author_attestation","sign_citation":"https://pith.science/pith/JBRWY2ADSH47FPZ347OX6EMLHX/action/citation_signature","submit_replication":"https://pith.science/pith/JBRWY2ADSH47FPZ347OX6EMLHX/action/replication_record"}},"created_at":"2026-07-05T11:06:41.376225+00:00","updated_at":"2026-07-05T11:06:41.376225+00:00"}