- Complexity-aware fine-tuning
Andrey Goncharov, Daniil Vyazhev, Petr Sychev, Edvard Khalafyan, Alexey Zaytsev · Jun 26, 2025 · Citations: 0
Abstract shows limited direct human-feedback or evaluation-protocol detail; use as adjacent methodological context.
- $π$-CoT: Prolog-Initialized Chain-of-Thought Prompting for Multi-Hop Question-Answering
Chao Wan, Albert Gong, Mihir Mishra, Carl-Leander Henneking, Claas Beger · Jun 25, 2025 · Citations: 0
Extensive experiments demonstrate that π-CoT significantly outperforms standard RAG and in-context CoT on multi-hop question-answering benchmarks.
- An Agentic System for Rare Disease Diagnosis with Traceable Reasoning
Weike Zhao, Chaoyi Wu, Yanjie Fan, Xiaoman Zhang, Pengcheng Qiu · Jun 25, 2025 · Citations: 0
Expert Verification Multi Agent
Here we present DeepRare, a multi-agent system for rare disease differential diagnosis decision support powered by large language models, integrating over 40 specialized tools and up-to-date knowledge sources.
- Programming by Backprop: An Instruction is Worth 100 Examples When Finetuning LLMs
Jonathan Cook, Silvia Sapora, Arash Ahmadian, Akbir Khan, Tim Rocktaschel · Jun 23, 2025 · Citations: 0
Demonstrations
Though execution of instructions in training data remains less reliable than when instructions are given in-context, our results demonstrate that procedural knowledge can be noisily `programmed' into LLMs through PBB, with important…
- Parallel Continuous Chain-of-Thought with Jacobi Iteration
Haoyi Wu, Zhihao Teng, Kewei Tu · Jun 23, 2025 · Citations: 0
Abstract shows limited direct human-feedback or evaluation-protocol detail; use as adjacent methodological context.
- PersonalAI: A Systematic Comparison of Knowledge Graph Storage and Retrieval Approaches for Personalized LLM agents
Mikhail Menschikov, Dmitry Evseev, Victoria Dochkina, Ruslan Kostoev, Ilia Perepechkin · Jun 20, 2025 · Citations: 0
We evaluate our system on three benchmarks: TriviaQA, HotpotQA, DiaASQ and demonstrate that different memory and retrieval configurations yield optimal performance depending on the task.
- DistillNote: Toward a Functional Evaluation Framework of LLM-Generated Clinical Note Summaries
Heloisa Oss Boll, Antonio Oss Boll, Leticia Puttlitz Boll, Ameen Abu Hanna, Iacer Calixto · Jun 20, 2025 · Citations: 0
Expert Verification
This study introduces DistillNote, an evaluation framework for LLM summaries that targets their functional utility by applying the generated summary downstream in a complex clinical prediction task, explicitly quantifying how much…
- A Scoping Review of Synthetic Data Generation by Language Models in Biomedical Research and Application: Data Utility and Quality Perspectives
Hanshu Rao, Weisi Liu, Haohan Wang, I-Chan Huang, Zhe He · Jun 19, 2025 · Citations: 0
Evaluations were heterogeneous: intrinsic metrics (27.1\%), human-in-the-loop assessments (44.1\%), and LLM-based evaluations (13.6\%).
- Revela: Dense Retriever Learning via Language Modeling
Fengyu Cai, Tong Chen, Xinran Zhao, Sihao Chen, Hongming Zhang · Jun 19, 2025 · Citations: 0
We evaluate Revela on domain-specific (CoIR), reasoning-intensive (BRIGHT), and general-domain (BEIR) benchmarks across various retriever backbones.
- DeVisE: Behavioral Testing of Medical Large Language Models
Camila Zurdo Tagliabue, Heloisa Oss Boll, Aykut Erdem, Erkut Erdem, Iacer Calixto · Jun 18, 2025 · Citations: 0
Large language models (LLMs) are increasingly applied in clinical decision support, yet current evaluations rarely reveal whether their outputs reflect genuine medical reasoning or superficial correlations.
