arXiv (All)
open access
Causal Tracing of Audio-Text Fusion in Large Audio Language Models
Despite the strong performance of large audio language models (LALMs) in various tasks, exactly how and where they integrate acoustic features with textual context remains unclear. We adapt causal tracing to investigate the internal information flow of LALMs during audio comprehension. By conducting
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- MusTBench: Benchmarking and Advancing Temporal Grounding in Music LLMs#821455
- MISHAP-Bench: A Hallucination Benchmark for Large Audio-Language Models#1118966
- Architecture-Dependent Causal Transfer of Activation States Across Large Language Models#620747
- Architecture-Dependent Causal Transfer of Activation States Across Large Language Models#619068
- Can Large Audio Language Models Ignore Multilingual Distractors? An Evaluation of Their Selective Auditory Attention Capabilities#1014704
Record · ID 1064891
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive