- Why Diffusion Language Models Struggle with Truly Parallel (Non-Autoregressive) Decoding?
Pengxiang Li, Dilxat Muhtar, Lu Yin, Tianlong Chen, Shiwei Liu · Feb 26, 2026 · Citations: 0
Automatic Metrics
Across math reasoning benchmarks, NAP yields stronger performance under parallel decoding than DLMs trained on standard long CoT data, with gains growing as parallelism increases.
- Toward Automatic Filling of Case Report Forms: A Case Study on Data from an Italian Emergency Department
Gabriela Anna Kaczmarek, Pietro Ferrazzi, Lorenzo Porta, Vicky Rubini, Bernardo Magnini · Feb 26, 2026 · Citations: 0
Automatic Metrics
We provide an analysis of the data, define the CRF-filling task and metric for its evaluation, and report on pilot experiments where we use an open-source state-of-the-art LLM to automatically execute the task.
- TCM-DiffRAG: Personalized Syndrome Differentiation Reasoning Method for Traditional Chinese Medicine based on Knowledge Graph and Chain of Thought
Jianmin Li, Ying Chang, Su-Kit Tang, Yujia Liu, Yanwen Wang · Feb 26, 2026 · Citations: 0
Automatic Metrics
Additionally, TCM-DiffRAG outperformed directly supervised fine-tuned (SFT) LLMs and other benchmark RAG methods.
- TherapyProbe: Generating Design Knowledge for Relational Safety in Mental Health Chatbots Through Adversarial Simulation
Joydeep Chandra, Satyam Kumar Navneet, Yong Zhang · Feb 26, 2026 · Citations: 0
Expert Verification Simulation Env Multi Agent
As mental health chatbots proliferate to address the global treatment gap, a critical question emerges: How do we design for relational safety the quality of interaction patterns that unfold across conversations rather than the correctness
- TabDLM: Free-Form Tabular Data Generation via Joint Numerical-Language Diffusion
Donghong Cai, Jiarui Feng, Yanbo Wang, Da Zheng, Yixin Chen · Feb 26, 2026 · Citations: 0
Automatic Metrics
Extensive experiments on diverse benchmarks demonstrate the effectiveness of TabDLM compared to strong diffusion- and LLM-based baselines.
- Strategy Executability in Mathematical Reasoning: Leveraging Human-Model Differences for Effective Guidance
Weida Liang, Yiyou Sun, Shuyuan Nan, Chuang Li, Dawn Song · Feb 26, 2026 · Citations: 0
Automatic Metrics
Through a controlled analysis of paired human-written and model-generated solutions, we identify a systematic dissociation between usage and executability: human- and model-derived strategies differ in structured, domain-dependent ways, lea
- Importance of Prompt Optimisation for Error Detection in Medical Notes Using Language Models
Craig Myles, Patrick Schrempf, David Harris-Birtill · Feb 25, 2026 · Citations: 0
Automatic Metrics
We show that automatic prompt optimisation with Genetic-Pareto (GEPA) improves error detection over the baseline accuracy performance from 0.669 to 0.785 with GPT-5 and 0.578 to 0.690 with Qwen3-32B, approaching the performance of medical d
- Dynamic Personality Adaptation in Large Language Models via State Machines
Leon Pielage, Ole Hätscher, Mitja Back, Bernhard Marschall, Benjamin Risse · Feb 25, 2026 · Citations: 0
Simulation Env
This work demonstrates the feasibility of modular, personality-adaptive architectures for education, customer support, and broader human-computer interaction.
- MEDSYN: Benchmarking Multi-EviDence SYNthesis in Complex Clinical Cases for Multimodal Large Language Models
Boqi Chen, Xudong Liu, Jiachuan Peng, Marianne Frey-Marti, Bang Zheng · Feb 25, 2026 · Citations: 0
Expert Verification Automatic Metrics
Multimodal large language models (MLLMs) have shown great potential in medical applications, yet existing benchmarks inadequately capture real-world clinical complexity.
- Multi-dimensional Assessment and Explainable Feedback for Counselor Responses to Client Resistance in Text-based Counseling with LLMs
Anqi Li, Ruihan Wang, Zhaoming Chen, Yuqian Chen, Yu Lu · Feb 25, 2026 · Citations: 0
Automatic Metrics
Although current NLP research has examined overall counseling quality and general therapeutic skills, it fails to provide granular evaluations of high-stakes moments where clients exhibit resistance.
- MrBERT: Modern Multilingual Encoders via Vocabulary, Domain, and Dimensional Adaptation
Daniel Tamayo, Iñaki Lacunza, Paula Rivera-Hidalgo, Severino Da Dalt, Javier Aula-Blasco · Feb 24, 2026 · Citations: 0
Automatic Metrics
We introduce MrBERT, a family of 150M-300M parameter encoders built on the ModernBERT architecture and pre-trained on 35 languages and code.
- Small Language Models for Privacy-Preserving Clinical Information Extraction in Low-Resource Languages
Mohammadreza Ghaffarzadeh-Esfahani, Nahid Yousefian, Ebrahim Heidari-Farsani, Ali Akbar Omidvarian, Sepehr Ghahraei · Feb 24, 2026 · Citations: 0
Automatic Metrics
Extracting clinical information from medical transcripts in low-resource languages remains a significant challenge in healthcare natural language processing (NLP).
- PVminer: A Domain-Specific Tool to Detect the Patient Voice in Patient Generated Data
Samah Fodeh, Linhai Ma, Yan Wang, Srivani Talakokkul, Ganesh Puthiaraju · Feb 24, 2026 · Citations: 0
Automatic Metrics
Patient-generated text such as secure messages, surveys, and interviews contains rich expressions of the patient voice (PV), reflecting communicative behaviors and social determinants of health (SDoH).
- MedCLIPSeg: Probabilistic Vision-Language Adaptation for Data-Efficient and Generalizable Medical Image Segmentation
Taha Koleilat, Hojat Asgariandehkordi, Omid Nejati Manzari, Berardino Barile, Yiming Xiao · Feb 23, 2026 · Citations: 0
Automatic Metrics
Medical image segmentation remains challenging due to limited annotations for training, ambiguous anatomical features, and domain shifts.
- An artificial intelligence framework for end-to-end rare disease phenotyping from clinical notes using large language models
Cathy Shyr, Yan Hu, Rory J. Tinker, Thomas A. Cassini, Kevin W. Byram · Feb 23, 2026 · Citations: 0
Expert Verification Automatic Metrics
Existing artificial intelligence approaches typically optimize individual components of phenotyping but do not operationalize the full clinical workflow of extracting features from clinical text, standardizing them to Human Phenotype Ontolo
- To Reason or Not to: Selective Chain-of-Thought in Medical Question Answering
Zaifu Zhan, Min Zeng, Shuang Zhou, Yiran Song, Xiaoyi Chen · Feb 23, 2026 · Citations: 0
Automatic Metrics
Two open-source LLMs (Llama-3.1-8B and Qwen-2.5-7B) were evaluated on four biomedical QA benchmarks-HeadQA, MedQA-USMLE, MedMCQA, and PubMedQA.
- AgenticSum: An Agentic Inference-Time Framework for Faithful Clinical Text Summarization
Fahmida Liza Piya, Rahmatollah Beheshti · Feb 23, 2026 · Citations: 0
Human Eval
We present AgenticSum, an inference-time, agentic framework that separates context selection, generation, verification, and targeted correction to reduce hallucinated content.
- Exploring Anti-Aging Literature via ConvexTopics and Large Language Models
Lana E. Yeganova, Won G. Kim, Shubo Tian, Natalie Xie, Donald C. Comeau · Feb 23, 2026 · Citations: 0
Automatic Metrics
Common clustering and topic modeling approaches such as K-means or LDA remain sensitive to initialization and prone to local optima, limiting reproducibility and evaluation.
- Assessing Risks of Large Language Models in Mental Health Support: A Framework for Automated Clinical AI Red Teaming
Ian Steenstra, Paola Pedrelli, Weiyan Shi, Stacy Marsella, Timothy W. Bickmore · Feb 23, 2026 · Citations: 0
Red Team Simulation Env
Large Language Models (LLMs) are increasingly utilized for mental health support; however, current safety benchmarks often fail to detect the complex, longitudinal risks inherent in therapeutic dialogue.
- SHIELD: Semantic Heterogeneity Integrated Embedding for Latent Discovery in Clinical Trial Safety Signals
Francois Vandenhende, Anna Georgiou, Theodoros Psaras, Ellie Karekla · Feb 23, 2026 · Citations: 0
Automatic Metrics
We present SHIELD, a novel methodology for automated and integrated safety signal detection in clinical trials.
- AgenticRAGTracer: A Hop-Aware Benchmark for Diagnosing Multi-Step Retrieval Reasoning in Agentic RAG
Qijie You, Wenkai Yu, Wentao Zhang · Feb 22, 2026 · Citations: 0
Automatic Metrics Long Horizon
With the rapid advancement of agent-based methods in recent years, Agentic RAG has undoubtedly become an important research direction.
- EvalSense: A Framework for Domain-Specific LLM (Meta-)Evaluation
Adam Dejl, Jonathan Pearson · Feb 21, 2026 · Citations: 0
Automatic Metrics
Robust and comprehensive evaluation of large language models (LLMs) is essential for identifying effective LLM system configurations and mitigating risks associated with deploying LLMs in sensitive domains.
- Think$^{2}$: Grounded Metacognitive Reasoning in Large Language Models
Abraham Paul Elenjical, Vivek Hruday Kavuri, Vasudeva Varma · Feb 21, 2026 · Citations: 0
Pairwise Preference Human Eval
We introduce a psychologically grounded metacognitive framework that operationalizes Ann Brown's regulatory cycle (Planning, Monitoring, and Evaluation) as a structured prompting architecture, and study its integration within a lightweight
- DP-RFT: Learning to Generate Synthetic Text via Differentially Private Reinforcement Fine-Tuning
Fangyuan Xu, Sihao Chen, Zinan Lin, Taiwei Shi, Sydney Graham · Feb 20, 2026 · Citations: 0
Automatic Metrics
Differentially private (DP) synthetic data generation plays a pivotal role in developing large language models (LLMs) on private data, where data owners cannot provide eyes-on access to individual examples.
- CUICurate: A GraphRAG-based Framework for Automated Clinical Concept Curation for NLP applications
Victoria Blake, Mathew Miller, Jamie Novak, Sze-yuan Ooi, Blanca Gallego · Feb 20, 2026 · Citations: 0
Expert Verification Automatic Metrics
The framework was evaluated on five lexically heterogeneous clinical concepts against a manually curated benchmark and gold-standard concept sets.
- Condition-Gated Reasoning for Context-Dependent Biomedical Question Answering
Jash Rajesh Parekh, Wonbin Kweon, Joey Chan, Rezarta Islamaj, Robert Leaman · Feb 20, 2026 · Citations: 0
Automatic Metrics
Existing benchmarks do not evaluate such conditional reasoning, and retrieval-augmented or graph-based methods lack explicit mechanisms to ensure that retrieved knowledge is applicable to given context.
- Bridging the Domain Divide: Supervised vs. Zero-Shot Clinical Section Segmentation from MIMIC-III to Obstetrics
Baris Karacan, Barbara Di Eugenio, Patrick Thornton · Feb 19, 2026 · Citations: 0
Automatic Metrics
Clinical free-text notes contain vital patient information.
- Small LLMs for Medical NLP: a Systematic Analysis of Few-Shot, Constraint Decoding, Fine-Tuning and Continual Pre-Training in Italian
Pietro Ferrazzi, Mattia Franzin, Alberto Lavelli, Bernardo Magnini · Feb 19, 2026 · Citations: 0
Automatic Metrics
Large Language Models (LLMs) consistently excel in diverse medical Natural Language Processing (NLP) tasks, yet their substantial computational requirements often limit deployment in real-world healthcare settings.
- What Makes a Good Doctor Response? An Analysis on a Romanian Telemedicine Platform
Adrian Cosma, Cosmin Dumitrache, Emilian Radoi · Feb 19, 2026 · Citations: 0
Expert Verification Automatic Metrics
As platforms increasingly rely on patient ratings and feedback, clinicians face growing pressure to maintain satisfaction scores, even though these evaluations often reflect communication quality more than clinical accuracy.
- ReIn: Conversational Error Recovery with Reasoning Inception
Takyoung Kim, Jinseok Nam, Chandrayee Basu, Xing Fan, Chengyuan Ma · Feb 19, 2026 · Citations: 0
Automatic Metrics
Conversational agents powered by large language models (LLMs) with tool integration achieve strong performance on fixed task-oriented dialogue datasets but remain vulnerable to unanticipated, user-induced errors.
- BanglaSummEval: Reference-Free Factual Consistency Evaluation for Bangla Summarization
Ahmed Rafid, Rumman Adib, Fariya Ahmed, Ajwad Abrar, Mohammed Saidul Islam · Feb 18, 2026 · Citations: 0
Automatic Metrics
However, most existing evaluation metrics overlook Bangla, a widely spoken yet under-resourced language, and often depend on reference summaries.
- Lyapunov Spectral Analysis of Speech Embedding Trajectories in Psychosis
Jelena Vasic, Branislav Andjelic, Ana Mancic, Dusica Filipovic Djurdjevic, Ljiljana Mihic · Feb 18, 2026 · Citations: 0
Automatic Metrics
We analyze speech embeddings from structured clinical interviews of psychotic patients and healthy controls by treating language production as a high-dimensional dynamical process.
- CLAA: Cross-Layer Attention Aggregation for Accelerating LLM Prefill
Bradley McDanel, Steven Li, Harshit Khaitan · Feb 17, 2026 · Citations: 0
Automatic Metrics
This oracle reveals that existing heuristics exhibit high variance across layers: rankings can degrade sharply at specific layers, a failure mode invisible to end-to-end benchmarks.
- Multi-Objective Alignment of Language Models for Personalized Psychotherapy
Mehrab Beikzadeh, Yasaman Asadollah Salmanpour, Ashima Suvarna, Sriram Sankararaman, Matteo Malgaroli · Feb 17, 2026 · Citations: 0
Pairwise PreferenceExpert Verification Automatic Metrics
While AI systems show therapeutic promise, current alignment approaches optimize objectives independently, failing to balance patient preferences with clinical safety.
- Evidence-Grounded Subspecialty Reasoning: Evaluating a Curated Clinical Intelligence Layer on the 2025 Endocrinology Board-Style Examination
Amir Hosseinian, MohammadReza Zare Shahneh, Umer Mansoor, Gilbert Szeto, Kirill Karlin · Feb 17, 2026 · Citations: 0
Automatic Metrics
Results: Mirror achieved 87.5% accuracy (105/120; 95% CI: 80.4-92.3%), exceeding a human reference of 62.3% and frontier LLMs including GPT-5.2 (74.6%), GPT-5 (74.0%), and Gemini-3-Pro (69.8%).
- LLM-to-Speech: A Synthetic Data Pipeline for Training Dialectal Text-to-Speech Models
Ahmed Khaled Khamis, Hesham Ali · Feb 17, 2026 · Citations: 0
Automatic Metrics
Despite the advances in neural text to speech (TTS), many Arabic dialectal varieties remain marginally addressed, with most resources concentrated on Modern Spoken Arabic (MSA) and Gulf dialects, leaving Egyptian Arabic -- the most widely u
- Clinically Inspired Symptom-Guided Depression Detection from Emotion-Aware Speech Representations
Chaithra Nerella, Chiranjeevi Yarra · Feb 17, 2026 · Citations: 0
Automatic Metrics
Depression manifests through a diverse set of symptoms such as sleep disturbance, loss of interest, and concentration difficulties.
- Towards Expectation Detection in Language: A Case Study on Treatment Expectations in Reddit
Aswathy Velutharambath, Amelie Wührl · Feb 17, 2026 · Citations: 0
Automatic Metrics
Patients' expectations towards their treatment have a substantial effect on the treatments' success.
- Cold-Start Personalization via Training-Free Priors from Structured World Models
Avinandan Bose, Shuyue Stella Li, Faeze Brahman, Pang Wei Koh, Simon Shaolei Du · Feb 16, 2026 · Citations: 0
Pairwise Preference Automatic Metrics
Cold-start personalization requires inferring user preferences through interaction when no user-specific historical data is available.
- Breaking Data Efficiency Dilemma: A Federated and Augmented Learning Framework For Alzheimer's Disease Detection via Speech
Xiao Wei, Bin Wen, Yuqin Lin, Kai Li, Mingyang gu · Feb 16, 2026 · Citations: 0
Automatic Metrics
Early diagnosis of Alzheimer's Disease (AD) is crucial for delaying its progression.
- Does Socialization Emerge in AI Agent Society? A Case Study of Moltbook
Ming Li, Xirui Li, Tianyi Zhou · Feb 15, 2026 · Citations: 0
Simulation Env Multi Agent
As large language model agents increasingly populate networked environments, a fundamental question arises: do artificial intelligence (AI) agent societies undergo convergence dynamics similar to human social systems?
- INSURE-Dial: A Phase-Aware Conversational Dataset & Benchmark for Compliance Verification and Phase Detection
Shubham Kulkarni, Alexander Lyzhov, Preetam Joshi, Shiva Chaitanya · Jan 28, 2026 · Citations: 0
Automatic Metrics Web Browsing
We introduce INSURE-Dial, to our knowledge the first public benchmark for developing and assessing compliance-aware voice agents for phase-aware call auditing with span-based compliance verification.
- Building Safe and Deployable Clinical Natural Language Processing under Temporal Leakage Constraints
Ha Na Cho, Sairam Sutari, Alexander Lopez, Hansen Bow, Kai Zheng · Jan 24, 2026 · Citations: 0
Automatic Metrics
Such behavior poses substantial risks for real-world deployment, where overconfident or temporally invalid predictions can disrupt clinical workflows and compromise patient safety.
- Stabilizing Off-Policy Training for Long-Horizon LLM Agent via Turn-Level Importance Sampling and Clipping-Triggered Normalization
Chenliang Li, Adel Elmahdy, Alex Boyd, Zhongruo Wang, Siliang Zeng · Nov 25, 2025 · Citations: 0
Automatic Metrics Long Horizon
Reinforcement learning (RL) algorithms such as PPO and GRPO are widely used to train large language models (LLMs) for multi-turn agentic tasks.
- From Medical Records to Diagnostic Dialogues: A Clinical-Grounded Approach and Dataset for Psychiatric Comorbidity
Tianxi Wan, Jiaming Luo, Siyuan Chen, Kunyao Lan, Jianhua Chen · Oct 29, 2025 · Citations: 0
Automatic Metrics Multi Agent
To address this, we develop a novel approach integrating synthetic patient electronic medical record (EMR) construction and multi-agent diagnostic dialogue generation.
- A Multi-faceted Analysis of Cognitive Abilities: Evaluating Prompt Methods with Large Language Models on the CONSORT Checklist
Sohyeon Jeon, Hyung-Chul Lee · Oct 22, 2025 · Citations: 0
Automatic Metrics
Despite the rapid expansion of Large Language Models (LLMs) in healthcare, robust and explainable evaluation of their ability to assess clinical trial reporting according to CONSORT standards remains an open challenge.
- PeruMedQA: Benchmarking Large Language Models (LLMs) on Peruvian Medical Exams -- Dataset Construction and Evaluation
Rodrigo M. Carrillo-Larco, Jesus Lovón Melgarejo, Manuel Castillo-Cara, Gusseppe Bravo-Rocca · Sep 15, 2025 · Citations: 0
Automatic Metrics
BACKGROUND: Medical large language models (LLMs) have demonstrated remarkable performance in answering medical examinations.
- LiveMCPBench: Can Agents Navigate an Ocean of MCP Tools?
Guozhao Mo, Wenliang Zhong, Jiawei Chen, Qianhao Yuan, Xuanang Chen · Aug 3, 2025 · Citations: 0
Automatic Metrics Tool Use
Unfortunately, there is still a large gap between real-world MCP usage and current evaluation: they typically assume single-server settings and directly inject tools into the model's context, bypassing the challenges of large-scale retrieva
- 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 Llm As Judge
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 predictio
- 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
Automatic Metrics
Evaluations were heterogeneous: intrinsic metrics (27.1\%), human-in-the-loop assessments (44.1\%), and LLM-based evaluations (13.6\%).
- 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
Automatic Metrics
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.
- Multimodal Integrated Knowledge Transfer to Large Language Models through Preference Optimization with Biomedical Applications
Zhanliang Wang, Da Wu, Quan Nguyen, Zhuoran Xu, Kai Wang · May 9, 2025 · Citations: 0
Pairwise Preference Automatic Metrics
To address this challenge, we introduce MINT (Multimodal Integrated kNowledge Transfer), a framework that aligns unimodal large decoder models with domain-specific decision patterns from multimodal biomedical data through preference optimiz
- m1: Unleash the Potential of Test-Time Scaling for Medical Reasoning with Large Language Models
Xiaoke Huang, Juncheng Wu, Hui Liu, Xianfeng Tang, Yuyin Zhou · Apr 1, 2025 · Citations: 0
Automatic Metrics
Our evaluation across diverse medical tasks demonstrates that test-time scaling consistently enhances medical reasoning, enabling lightweight fine-tuned models under 10B parameters to establish new state-of-the-art performance, while our 32
- A Scalable Framework for Evaluating Health Language Models
Neil Mallinar, A. Ali Heydari, Xin Liu, Anthony Z. Faranesh, Brent Winslow · Mar 30, 2025 · Citations: 0
Rubric RatingExpert Verification Automatic Metrics
As LLM-driven health applications are increasingly adopted, rigorous and efficient one-sided evaluation methodologies are crucial to ensure response quality across multiple dimensions, including accuracy, personalization and safety.
- MedPlan: A Two-Stage RAG-Based System for Personalized Medical Plan Generation
Hsin-Ling Hsu, Cong-Tinh Dao, Luning Wang, Zitao Shuai, Thao Nguyen Minh Phan · Mar 23, 2025 · Citations: 0
Expert Verification Automatic Metrics
Comprehensive evaluation demonstrates that our method significantly outperforms baseline approaches in both assessment accuracy and treatment plan quality.
- Integrating Chain-of-Thought and Retrieval Augmented Generation Enhances Rare Disease Diagnosis from Clinical Notes
Zhanliang Wang, Da Wu, Quan Nguyen, Kai Wang · Mar 15, 2025 · Citations: 0
Automatic Metrics
These studies typically use Human Phenotype Ontology (HPO) terms to prompt foundation models like GPT and LLaMA to predict candidate genes.
- Compressing Language Models for Specialized Domains
Miles Williams, George Chrysostomou, Vitor Jeronymo, Nikolaos Aletras · Feb 25, 2025 · Citations: 0
Automatic Metrics
Compression techniques such as pruning and quantization offer a practical path towards efficient LM deployment, exemplified by their ability to preserve performance on general-purpose benchmarks.
- Can Multimodal LLMs Perform Time Series Anomaly Detection?
Xiongxiao Xu, Haoran Wang, Yueqing Liang, Philip S. Yu, Yue Zhao · Feb 25, 2025 · Citations: 0
Automatic Metrics Multi Agent
One natural way for humans to detect time series anomalies is through visualization and textual description.
- Moving Beyond Medical Exams: A Clinician-Annotated Fairness Dataset of Real-World Tasks and Ambiguity in Mental Healthcare
Max Lamparth, Declan Grabb, Amy Franks, Scott Gershan, Kaitlyn N. Kunstman · Feb 22, 2025 · Citations: 0
Pairwise PreferenceExpert Verification Automatic Metrics
Current medical language model (LM) benchmarks often over-simplify the complexities of day-to-day clinical practice tasks and instead rely on evaluating LMs on multiple-choice board exam questions.
- Dialogue is Better Than Monologue: Instructing Medical LLMs via Strategical Conversations
Zijie Liu, Xinyu Zhao, Jie Peng, Zhuangdi Zhu, Qingyu Chen · Jan 29, 2025 · Citations: 0
Automatic MetricsSimulation Env
These tuning methods and benchmarks overlook critical aspects like evidence-based reasoning and handling distracting information.
