Lost in Speech: Trilingual Spoken Hallucination Detection Across Audio and Transcripts
Trilingual spoken hallucination detection, comparing what is detectable from raw audio against what survives transcription.
meruyert-aristombayeva
Dongwon Lee
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1 min read
AOR-Bench: Do Large Audio Language Models Over-Refuse Pseudo-Harmful Queries?
A benchmark for over-refusal in large audio language models — how often they decline pseudo-harmful but benign spoken queries, and what drives it.
jiaxi-yang
Position: Breaking the Dual Curse of Multilingual AI Requires Socio-Technical Guardrails, Not Post-Hoc Alignment
A position paper arguing that the dual curse of multilingual AI — 35% harmful generation and near-random reward-model accuracy in low-resource languages — cannot be fixed by …
DIA-HARM: Dialectal Disparities in Harmful Content Detection Across 50 English Dialects
DIA-HARM evaluates 16 harmful content detection models across 50 English dialects using 195K+ samples, revealing 1.4–3.6% F1 drops for fine-tuned models and up to 27% for zero-shot …
BLUFF: Benchmarking in Low-resoUrce Languages for detecting Falsehoods and Fake news
BLUFF is the largest multilingual fake news detection benchmark, spanning 79 languages with 202K+ samples. It introduces AXL-CoI for adversarial generation and mPURIFY for quality …
Beyond speculation: Measuring the Growing Presence of LLM-generated texts in Multilingual Disinformation
This IEEE article provides empirical measurements of LLM-generated texts in multilingual disinformation, moving beyond speculation to analyze the growing presence and …
dominik-macko
Generative AI Disproportionately Harms Long Tail Users
This Computer article examines how Generative AI disproportionately harms longtail users, focusing on the structural inequalities that emerge when AI systems are deployed without …
barani-maung-maung
The Longtail Impact of Generative AI on Disinformation: Harmonizing Dichotomous Perspectives
This IEEE Intelligent Systems article examines the "longtail" impact of Generative AI on disinformation in high-impact events and resource-limited settings. We analyze four …
Authorship Obfuscation in Multilingual Machine-Generated Text Detection
This research from Penn State and KiNiT, benchmarks the effectiveness of 10 authorship obfuscation (AO) techniques against 37 machine-generated text (MGT) detection methods across …
dominik-macko
Fighting Fire with Fire - EMNLP 2023
The Dual Role of LLMs in Crafting and Detecting Elusive Disinformation
jason-lucas