Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
HSSBench: Benchmarking Humanities and Social Sciences Ability for Multimodal Large Language Models
As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2506.03922.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-15T23:21:12.998437Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-04T17:29:59.531643Z
Reference resolution
0 of 0 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation cc4463f7-9f06-4b0f-add8-442fc11eea2e · inbound
Perception, Reason, Think, and Plan: A Survey on Large Multimodal Reasoning Models cites this paper.
Perception, Reason, Think, and Plan: A Survey on Large Multimodal Reasoning Models HSSBench: Benchmarking Humanities and Social Sciences Ability for Multimodal Large Language Models
Reference 207
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T23:21:12.998437Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 45c223d0-eb99-4368-90ca-c3fc613922f9 · inbound
KAME: Tandem Architecture for Enhancing Knowledge in Real-Time Speech-to-Speech Conversational AI cites this paper.
KAME: Tandem Architecture for Enhancing Knowledge in Real-Time Speech-to-Speech Conversational AI HSSBench: Benchmarking Humanities and Social Sciences Ability for Multimodal Large Language Models
Reference 24
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T15:49:53.978211Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6b5301ed-f230-46c9-b5e6-a0b5cc23ad5f · inbound
Better Eyes, Better Thoughts: Why Vision Chain-of-Thought Fails in Medicine cites this paper.
Better Eyes, Better Thoughts: Why Vision Chain-of-Thought Fails in Medicine HSSBench: Benchmarking Humanities and Social Sciences Ability for Multimodal Large Language Models
Reference 10
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-08-12T02:23:50.971990Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation bd8cc177-28b7-40c9-a578-96508a619b44 · inbound
Agentic World Modeling: Foundations, Capabilities, Laws, and Beyond cites this paper.
Agentic World Modeling: Foundations, Capabilities, Laws, and Beyond HSSBench: Benchmarking Humanities and Social Sciences Ability for Multimodal Large Language Models
Reference 171
- Resolution
- verified exact
- arxiv_id, observed 2026-08-12T02:23:50.971990Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 45873610-c958-4a40-8b84-4db700ad89e1 · inbound
Agentic World Modeling: Foundations, Capabilities, Laws, and Beyond cites this paper.
Agentic World Modeling: Foundations, Capabilities, Laws, and Beyond HSSBench: Benchmarking Humanities and Social Sciences Ability for Multimodal Large Language Models
Reference 171
- Resolution
- verified exact
- arxiv_id, observed 2026-08-12T02:23:50.971990Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation c3d0a8d3-b80a-4149-81f1-88b93ac0756e · inbound
BenCSSmark: Making the Social Sciences Count in LLM Research cites this paper.
BenCSSmark: Making the Social Sciences Count in LLM Research HSSBench: Benchmarking Humanities and Social Sciences Ability for Multimodal Large Language Models
Reference 9
- Resolution
- verified exact
- arxiv_id, observed 2026-08-12T02:23:50.971990Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation d761669d-a7f3-482b-a0e8-b8b0b6c6f9eb · inbound
Can LLMs Think Like Consumers? Benchmarking Crowd-Level Reaction Reconstruction with ConsumerSimBench cites this paper.
Can LLMs Think Like Consumers? Benchmarking Crowd-Level Reaction Reconstruction with ConsumerSimBench HSSBench: Benchmarking Humanities and Social Sciences Ability for Multimodal Large Language Models
Reference 72
- Resolution
- verified exact
- arxiv_id, observed 2026-08-12T02:23:50.971990Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation e18acb3e-7388-4a86-a7c2-219f0e7a4b2c · inbound
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving cites this paper.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving HSSBench: Benchmarking Humanities and Social Sciences Ability for Multimodal Large Language Models
Reference 61
- Resolution
- verified exact
- arxiv_id, observed 2026-08-12T02:23:50.971990Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 45a9b7c3-7ce1-40dd-8ffe-f8184af67398 · inbound
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving cites this paper.
DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving HSSBench: Benchmarking Humanities and Social Sciences Ability for Multimodal Large Language Models
Reference 61
- Resolution
- verified exact
- arxiv_id, observed 2026-08-12T02:23:50.971990Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation d30b77b3-aa77-406f-8e46-e568ea9681e5 · inbound
NormAct: Benchmarking Embodied Agents' Proactive Compliance with Unspoken Social Norms cites this paper.
NormAct: Benchmarking Embodied Agents' Proactive Compliance with Unspoken Social Norms HSSBench: Benchmarking Humanities and Social Sciences Ability for Multimodal Large Language Models
Reference 29
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-08-12T02:23:50.971990Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.