Researchers introduced AgentFactory, a framework that jointly optimizes foundation models and workflow structures in agentic systems while considering performance, cost, and efficiency. In evaluations…
Researchers introduced Prompt Embedding Probes (PEP), a white-box method for answer-level hallucination detection in large language models that augments standard linear probes with learnable prompt em…
Researchers introduced FLARE (Few-shot Learning-based Adaptive Reflective Engine), a framework that uses reflective mechanisms and few-shot reference examples to optimize prompts for large language mo…
A new training-time framework called Dependency-Aware Intermediate QA Supervision (DAIS) improves final-answer accuracy on complex reasoning tasks by converting filtered teacher rationales into stage-…
A new multi-agent framework called GraphDx improves diagnostic success rates from 50-68% to 79-93% while reducing test costs by 20-54%, according to a preprint on arXiv (2607.15280v1). The knowledge-e…
Anthropic's Claude Fable 5, the company's most capable publicly available model, achieves top-tier accuracy on eight biomedical benchmarks but refuses to answer between 8.0% and 99.4% of questions dep…
BiRG-LoRA, a single-adapter rank-gated method, achieves 69.31% macro-average accuracy on medical QA benchmarks while using 28.1% fewer parameters than MoELoRA, offering a more efficient and accurate A…
Researchers introduced CoRA, a GRPO-based reinforcement learning framework that aligns LLM confidence with rationale quality in chain-of-thought reasoning. Across MedQA, MathQA, and OpenBookQA, CoRA r…