Agents8 min read
Google launches official Developer Knowledge API for AI agents
Google released an API ecosystem to replace web scraping with structured documentation access.
From Google AI developers blog
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Agents8 min read
Google released an API ecosystem to replace web scraping with structured documentation access.
From Google AI developers blog
AI1 min read
Madison, a server in New York City, greets every table by asking about each diner's allergies. Lately, there have been some close calls. "Sometimes people will tell me they have a shellfish allergy, and I'll come back, and they won't ask...
From The Verge AI
Photo: Yan Krukau
AI1 min read
America.gov is intended to simplify the process of navigating government bureaucracy, but language models are imperfect and remain prone to hallucinations, which could cause new issues.
From TechCrunch AI
AI1 min read
“It’s important for service members to understand the uncertainty inherent to LLMs," a GovAI research scholar warns.
From TechCrunch AI
Agents1 min read
TypeSafe launched Jev, a model trained with RLCD for decisions. It is significantly faster and cheaper than small frontier models.
From Latent Space
LLMs1 min read
A new study maps 22 LLMs across closed-source and open-source categories using self-reported personality traits projected into a six-dimensional archetype space.
From arXiv cs.CL
LLMs1 min read
arXiv:2609.12111v1 Announce Type: new Abstract: Factual hallucination in closed-book question answering is often treated as a coverage problem: a model fails because the relevant fact is absent from its internal memory. This view misses ...
From arXiv cs.CL
LLMs1 min read
Research reveals that large language models exhibit minimal disagreement with factual input when the context appears plausible, even when it contains counterfactual or fictional elements. This suggests a weaker-than-expected context-memory conflict in LLMs.
From arXiv cs.CL
Research1 min read
LexAgentHallu is a new benchmark designed to evaluate legal agent hallucinations across multi-step trajectories. The benchmark contains 3414 instances with detailed annotation and metrics, revealing patterns in agentic failures that are invisible with standard outcome-level evaluations.
From arXiv cs.AI
LLMs1 min read
Large language models exhibit a deceptive failure mode when auditing documents, producing confident fabrications in large batches. This research highlights the need for bounded batch sizes and mechanical verification for reliable document quality assessment.
From arXiv cs.CL
LLMs1 min read
arXiv:2609.04404v1 Announce Type: new Abstract: ASR systems sometimes produce fluent text that is unrelated to the speech they receive. We view these hallucinations as one possible consequence of a broader grounding failure, in which the...
From arXiv cs.CL
Research1 min read
A training-free method using low-rank projection of decoder activations significantly lowers hallucination rates in Whisper during inference, with minimal impact on speech recognition accuracy.
From arXiv cs.AI
LLMs1 min read
GRACE deconstructs LLM responses into claims, grounds them against knowledge priors, and classifies their validity, enabling efficient expert verification and knowledge expansion.
From arXiv cs.CL
Posts are drafted from public feeds by models OpenSmartRoute routes to - the same router, skill and metering customers use - and always link to the original source. Corrections: support.
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