Accuracy Metric Papers

Researcher Quick Triage

Use this page to compare metric behavior across protocols and benchmarks before selecting your reporting stack. Quality band: High .

• 60 papers are not low-signal flagged in this sample.
• Use the protocol matrix below to avoid comparing metrics across incompatible eval setups.

Primary action: Use the top metric-reliable papers first, then compare benchmark context in the matrix before drawing conclusions.

Start Here (Metric-Reliable First 6)

Ranked for metric reporting completeness and comparability.

• MinerU2.5-Pro: Pushing the Limits of Data-Centric Document Parsing at Scale

  Apr 6, 2026 · Citations: 0 · Score: 9.5

  Metrics: Accuracy · Eval: Automatic Metrics

• Personalized RewardBench: Evaluating Reward Models with Human Aligned Personalization

  Apr 8, 2026 · Citations: 0 · Score: 9.0

  Metrics: Accuracy, Helpfulness · Eval: Human Eval, Automatic Metrics

• TraceSafe: A Systematic Assessment of LLM Guardrails on Multi-Step Tool-Calling Trajectories

  Apr 8, 2026 · Citations: 0 · Score: 9.0

  Metrics: Accuracy · Eval: Automatic Metrics

• AfriVoices-KE: A Multilingual Speech Dataset for Kenyan Languages

  Apr 9, 2026 · Citations: 0 · Score: 8.0

  Metrics: Accuracy · Eval: Automatic Metrics

• Don't Overthink It: Inter-Rollout Action Agreement as a Free Adaptive-Compute Signal for LLM Agents

  Apr 9, 2026 · Citations: 0 · Score: 8.0

  Metrics: Accuracy · Eval: Automatic Metrics

• Training Data Size Sensitivity in Unsupervised Rhyme Recognition

  Apr 9, 2026 · Citations: 0 · Score: 8.0

  Metrics: Accuracy, Agreement · Eval: Automatic Metrics

Metric Protocol Matrix (Top 10)

Compare metric, benchmark, and evaluation context side by side.

Top Papers Reporting This Metric

• Act Wisely: Cultivating Meta-Cognitive Tool Use in Agentic Multimodal Models

  Shilin Yan, Jintao Tong, Hongwei Xue, Xiaojun Tang, Yangyang Wang · Apr 9, 2026 · Citations: 0

  Automatic Metrics General

  The advent of agentic multimodal models has empowered systems to actively interact with external environments.

• Cram Less to Fit More: Training Data Pruning Improves Memorization of Facts

  Jiayuan Ye, Vitaly Feldman, Kunal Talwar · Apr 9, 2026 · Citations: 0

  Automatic Metrics Law

  Abstract shows limited direct human-feedback or evaluation-protocol detail; use as adjacent methodological context.

• What do Language Models Learn and When? The Implicit Curriculum Hypothesis

  Emmy Liu, Kaiser Sun, Millicent Li, Isabelle Lee, Lindia Tjuatja · Apr 9, 2026 · Citations: 0

  Automatic Metrics MathLaw

  Abstract shows limited direct human-feedback or evaluation-protocol detail; use as adjacent methodological context.

• SealQA: Raising the Bar for Reasoning in Search-Augmented Language Models

  Thinh Pham, Nguyen Nguyen, Pratibha Zunjare, Weiyuan Chen, Yu-Min Tseng · Jun 1, 2025 · Citations: 0

  Automatic Metrics General

  We introduce SealQA, a new challenge benchmark for evaluating SEarch-Augmented Language models on fact-seeking questions where web search yields conflicting, noisy, or unhelpful results.

• The Detection-Extraction Gap: Models Know the Answer Before They Can Say It

  Hanyang Wang, Mingxuan Zhu · Apr 8, 2026 · Citations: 0

  Automatic Metrics Coding

  Across five model configurations, two families, and three benchmarks, we find that 52--88% of chain-of-thought tokens are produced after the answer is recoverable from a partial prefix.

• Human-computer interactions predict mental health

  Veith Weilnhammer, Jefferson Ortega, David Whitney · Nov 25, 2025 · Citations: 0

  Automatic Metrics Medicine

  Here, we show that everyday human-computer interactions encode mental health with biomarker accuracy.

• AfriVoices-KE: A Multilingual Speech Dataset for Kenyan Languages

  Lilian Wanzare, Cynthia Amol, zekiel Maina, Nelson Odhiambo, Hope Kerubo · Apr 9, 2026 · Citations: 0

  Automatic Metrics Multilingual

  Quality assurance operated at multiple layers, encompassing automated signal-to-noise ratio validation prior to recording and human review for content accuracy.

• KV Cache Offloading for Context-Intensive Tasks

  Andrey Bocharnikov, Ivan Ermakov, Denis Kuznedelev, Vyacheslav Zhdanovskiy, Yegor Yershov · Apr 9, 2026 · Citations: 0

  Automatic Metrics General

  Prior evaluations have largely focused on tasks that do not require extracting large amounts of information from the context.

• Don't Overthink It: Inter-Rollout Action Agreement as a Free Adaptive-Compute Signal for LLM Agents

  Khushal Sethi · Apr 9, 2026 · Citations: 0

  Automatic Metrics Math

  We introduce TrACE (Trajectorical Adaptive Compute via agrEement), a training-free controller that allocates LLM calls adaptively across agent timesteps by measuring inter-rollout action agreement.

• Stacked from One: Multi-Scale Self-Injection for Context Window Extension

  Wei Han, Pan Zhou, Soujanya Poria, Shuicheng Yan · Mar 5, 2026 · Citations: 0

  Automatic Metrics General

  Across a comprehensive suite of long-context modeling and understanding benchmarks, \modelname~achieves performance superior or comparable to strong baselines, striking an optimal balance between efficiency and accuracy.

• Seeing Like an AI: How LLMs Apply (and Misapply) Wikipedia Neutrality Norms

  Joshua Ashkinaze, Ruijia Guan, Laura Kurek, Eytan Adar, Ceren Budak · Jul 4, 2024 · Citations: 0

  Human EvalAutomatic Metrics General

  We evaluate LLMs' capacity to detect (Task 1) and correct (Task 2) biased Wikipedia edits according to Wikipedia's Neutral Point of View (NPOV) policy.

• HyperMem: Hypergraph Memory for Long-Term Conversations

  Juwei Yue, Chuanrui Hu, Jiawei Sheng, Zuyi Zhou, Wenyuan Zhang · Apr 9, 2026 · Citations: 0

  Llm As JudgeAutomatic Metrics General

  Long-term memory is essential for conversational agents to maintain coherence, track persistent tasks, and provide personalized interactions across extended dialogues.

• HumanLLM: Benchmarking and Improving LLM Anthropomorphism via Human Cognitive Patterns

  Xintao Wang, Jian Yang, Weiyuan Li, Rui Xie, Jen-tse Huang · Jan 15, 2026 · Citations: 0

  Automatic MetricsSimulation Env Coding

  We present HumanLLM, a framework treating psychological patterns as interacting causal forces.

• Training Data Size Sensitivity in Unsupervised Rhyme Recognition

  Petr Plecháč, Artjoms Šeļa, Silvie Cinková, Mirella De Sisto, Lara Nugues · Apr 9, 2026 · Citations: 0

  Automatic Metrics Multilingual

  This complicates automated rhymed recognition and evaluation, especially in multilingual context.

• Quantum Vision Theory Applied to Audio Classification for Deepfake Speech Detection

  Khalid Zaman, Melike Sah, Anuwat Chaiwongyenc, Cem Direkoglu · Apr 9, 2026 · Citations: 0

  Automatic Metrics General

  Abstract shows limited direct human-feedback or evaluation-protocol detail; use as adjacent methodological context.

• TEC: A Collection of Human Trial-and-error Trajectories for Problem Solving

  Xinkai Zhang, Jingtao Zhan, Yiqun Liu, Qingyao Ai · Apr 8, 2026 · Citations: 0

  Automatic Metrics General

  Trial-and-error is a fundamental strategy for humans to solve complex problems and a necessary capability for Artificial Intelligence (AI) systems operating in real-world environments.

• Guaranteeing Knowledge Integration with Joint Decoding for Retrieval-Augmented Generation

  Zhengyi Zhao, Shubo Zhang, Zezhong Wang, Yuxi Zhang, Huimin Wang · Apr 9, 2026 · Citations: 0

  Automatic Metrics General

  Experiments on five QA benchmarks demonstrate that GuarantRAG improves accuracy by up to 12.1% and reduces hallucinations by 16.3% compared to standard and dynamic RAG baselines.

• MinerU2.5-Pro: Pushing the Limits of Data-Centric Document Parsing at Scale

  Bin Wang, Tianyao He, Linke Ouyang, Fan Wu, Zhiyuan Zhao · Apr 6, 2026 · Citations: 0

  Automatic Metrics General

  At its core is a Data Engine co-designed around coverage, informativeness, and annotation accuracy: Diversity-and-Difficulty-Aware Sampling expands training data from under 10M to 65.5M samples while mitigating distribution shift;…

• Paragraph Segmentation Revisited: Towards a Standard Task for Structuring Speech

  Fabian Retkowski, Alexander Waibel · Dec 30, 2025 · Citations: 0

  Automatic Metrics General

  First, we establish TEDPara (human-annotated TED talks) and YTSegPara (YouTube videos with synthetic labels) as the first benchmarks for the paragraph segmentation task.

• Kathleen: Oscillator-Based Byte-Level Text Classification Without Tokenization or Attention

  George Fountzoulas · Apr 9, 2026 · Citations: 0

  Automatic Metrics General

  Abstract shows limited direct human-feedback or evaluation-protocol detail; use as adjacent methodological context.

• SAT: Balancing Reasoning Accuracy and Efficiency with Stepwise Adaptive Thinking

  Weiyang Huang, Xuefeng Bai, Kehai Chen, Xinyang Chen, Yibin Chen · Apr 9, 2026 · Citations: 0

  Automatic Metrics General

  Experiments across 9 LRMs and 7 benchmarks show that SAT achieves up to 40% reduction in reasoning tokens while generally maintaining or improving accuracy.

• Which Way Does Time Flow? A Psychophysics-Grounded Evaluation for Vision-Language Models

  Shiho Matta, Lis Kanashiro Pereira, Peitao Han, Fei Cheng, Shigeru Kitazawa · Oct 30, 2025 · Citations: 0

  Automatic Metrics Coding

  We introduce AoT-PsyPhyBENCH, a psychophysically validated benchmark that tests whether VLMs can infer temporal direction in natural videos using the same stimuli and behavioral baselines established for humans.

• Hallucination Detection and Evaluation of Large Language Model

  Chenggong Zhang, Haopeng Wang, Hexi Meng · Dec 27, 2025 · Citations: 0

  Automatic Metrics General

  To address this, we integrate the Hughes Hallucination Evaluation Model (HHEM), a lightweight classification-based framework that operates independently of LLM-based judgments, significantly improving efficiency while maintaining high…

• Personalized RewardBench: Evaluating Reward Models with Human Aligned Personalization

  Qiyao Ma, Dechen Gao, Rui Cai, Boqi Zhao, Hanchu Zhou · Apr 8, 2026 · Citations: 0

  Human EvalAutomatic Metrics General

  Pluralistic alignment has emerged as a critical frontier in the development of Large Language Models (LLMs), with reward models (RMs) serving as a central mechanism for capturing diverse human values.

• Appear2Meaning: A Cross-Cultural Benchmark for Structured Cultural Metadata Inference from Images

  Yuechen Jiang, Enze Zhang, Md Mohsinul Kabir, Qianqian Xie, Stavroula Golfomitsou · Apr 8, 2026 · Citations: 0

  Llm As JudgeAutomatic Metrics General

  We introduce a multi-category, cross-cultural benchmark for this task and evaluate VLMs using an LLM-as-Judge framework that measures semantic alignment with reference annotations.

• Evaluating In-Context Translation with Synchronous Context-Free Grammar Transduction

  Jackson Petty, Jaulie Goe, Tal Linzen · Apr 8, 2026 · Citations: 0

  Automatic Metrics Multilingual

  Abstract shows limited direct human-feedback or evaluation-protocol detail; use as adjacent methodological context.

• A Systematic Study of Retrieval Pipeline Design for Retrieval-Augmented Medical Question Answering

  Nusrat Sultana, Abdullah Muhammad Moosa, Kazi Afzalur Rahman, Sajal Chandra Banik · Apr 8, 2026 · Citations: 0

  Automatic Metrics Medicine

  This study presents a systematic evaluation of retrieval-augmented medical question answering using the MedQA USMLE benchmark and a structured textbook-based knowledge corpus.

• ClickGuard: A Trustworthy Adaptive Fusion Framework for Clickbait Detection

  Chhavi Dhiman, Naman Chawla, Riya Dhami, Gaurav Kumar, Ganesh Naik · Apr 8, 2026 · Citations: 0

  Automatic Metrics Coding

  Abstract shows limited direct human-feedback or evaluation-protocol detail; use as adjacent methodological context.

• Joint Optimization of Reasoning and Dual-Memory for Self-Learning Diagnostic Agent

  Bingxuan Li, Simo Du, Yue Guo · Apr 8, 2026 · Citations: 0

  Automatic Metrics Medicine

  We propose SEA, a self-learning diagnostic agent with cognitively inspired dual-memory module.

• UI-AGILE: Advancing GUI Agents with Effective Reinforcement Learning and Precise Inference-Time Grounding

  Shuquan Lian, Yuhang Wu, Jia Ma, Yifan Ding, Zihan Song · Jul 29, 2025 · Citations: 0

  Automatic Metrics Coding

  The emergence of Multimodal Large Language Models (MLLMs) has driven significant advances in Graphical User Interface (GUI) agent capabilities.

• TraceSafe: A Systematic Assessment of LLM Guardrails on Multi-Step Tool-Calling Trajectories

  Yen-Shan Chen, Sian-Yao Huang, Cheng-Lin Yang, Yun-Nung Chen · Apr 8, 2026 · Citations: 0

  Automatic Metrics General

  As large language models (LLMs) evolve from static chatbots into autonomous agents, the primary vulnerability surface shifts from final outputs to intermediate execution traces.

• LaScA: Language-Conditioned Scalable Modelling of Affective Dynamics

  Kosmas Pinitas, Ilias Maglogiannis · Apr 8, 2026 · Citations: 0

  Automatic Metrics General

  Predicting affect in unconstrained environments remains a fundamental challenge in human-centered AI.

• Yale-DM-Lab at ArchEHR-QA 2026: Deterministic Grounding and Multi-Pass Evidence Alignment for EHR Question Answering

  Elyas Irankhah, Samah Fodeh · Apr 8, 2026 · Citations: 0

  Automatic Metrics Medicine

  Third, results on the development set show that alignment accuracy is mainly limited by reasoning.

• Graph Representation-based Model Poisoning on the Heterogeneous Internet of Agents

  Hanlin Cai, Houtianfu Wang, Haofan Dong, Kai Li, Sai Zou · Nov 10, 2025 · Citations: 0

  Automatic Metrics General

  Internet of Agents (IoA) envisions a unified, agent-centric paradigm where heterogeneous large language model (LLM) agents can interconnect and collaborate at scale.

• IndoBERT-Sentiment: Context-Conditioned Sentiment Classification for Indonesian Text

  Muhammad Apriandito Arya Saputra, Andry Alamsyah, Dian Puteri Ramadhani, Thomhert Suprapto Siadari, Hanif Fakhrurroja · Apr 8, 2026 · Citations: 0

  Automatic Metrics General

  In a head-to-head evaluation against three widely used general-purpose Indonesian sentiment models on the same test set, IndoBERT-Sentiment outperforms the best baseline by 35.6 F1 points.

• Gemma 4, Phi-4, and Qwen3: Accuracy-Efficiency Tradeoffs in Dense and MoE Reasoning Language Models

  Md Motaleb Hossen Manik, Ge Wang · Apr 8, 2026 · Citations: 0

  Automatic Metrics Math

  We present a controlled empirical benchmark of seven recent reasoning-oriented instruction-tuned models spanning dense and MoE designs, namely Gemma-4-E2B, Gemma-4-E4B, Gemma-4-26B-A4B, Phi-4-mini-reasoning, Phi-4-reasoning, Qwen3-8B, and…

• MARS: Enabling Autoregressive Models Multi-Token Generation

  Ziqi Jin, Lei Wang, Ziwei Luo, Aixin Sun · Apr 8, 2026 · Citations: 0

  Automatic Metrics General

  When generating one token per forward pass, MARS matches or exceeds the AR baseline on six standard benchmarks.

• iTAG: Inverse Design for Natural Text Generation with Accurate Causal Graph Annotations

  Wenshuo Wang, Boyu Cao, Nan Zhuang, Wei Li · Apr 8, 2026 · Citations: 0

  Automatic Metrics General

  This suggests that iTAG-generated data can serve as a practical surrogate for scalable benchmarking of text-based causal discovery algorithms.

• Do We Need Distinct Representations for Every Speech Token? Unveiling and Exploiting Redundancy in Large Speech Language Models

  Bajian Xiang, Tingwei Guo, Xuan Chen, Yang Han · Apr 8, 2026 · Citations: 0

  Automatic Metrics General

  Extensive evaluations across three tasks demonstrate that our approach reduces prefilling FLOPs by 27.48\% while maintaining competitive accuracy.

• MedDialBench: Benchmarking LLM Diagnostic Robustness under Parametric Adversarial Patient Behaviors

  Xiaotian Luo, Xun Jiang, Jiangcheng Wu · Apr 8, 2026 · Citations: 0

  Automatic Metrics Medicine

  Interactive medical dialogue benchmarks have shown that LLM diagnostic accuracy degrades significantly when interacting with non-cooperative patients, yet existing approaches either apply adversarial behaviors without graded severity or…

• Cognitive Loop of Thought: Reversible Hierarchical Markov Chain for Efficient Mathematical Reasoning

  Jia-Chen Zhang, Zheng Zhou, Yu-Jie Xiong · Apr 8, 2026 · Citations: 0

  Automatic Metrics Math

  Inspired by human cognitive processes, we introduce a backward verification mechanism at each hierarchical layer.

• Beyond Accuracy: Diagnosing Algebraic Reasoning Failures in LLMs Across Nine Complexity Dimensions

  Parth Patil, Dhruv Kumar, Yash Sinha, Murari Mandal · Apr 8, 2026 · Citations: 0

  Automatic Metrics General

  Algebraic reasoning remains one of the most informative stress tests for large language models, yet current benchmarks provide no mechanism for attributing failure to a specific cause.

• SimSiam Naming Game: A Unified Approach for Representation Learning and Emergent Communication

  Nguyen Le Hoang, Tadahiro Taniguchi, Fang Tianwei, Akira Taniguchi · Oct 29, 2024 · Citations: 0

  Automatic Metrics General

  Emergent Communication (EmCom) investigates how agents develop symbolic communication through interaction without predefined language.

• How Long Reasoning Chains Influence LLMs' Judgment of Answer Factuality

  Minzhu Tu, Shiyu Ni, Keping Bi · Apr 8, 2026 · Citations: 0

  Human EvalAutomatic Metrics Math

  Large language models (LLMs) has been widely adopted as a scalable surrogate for human evaluation, yet such judges remain imperfect and susceptible to surface-level biases.

• Select-then-Solve: Paradigm Routing as Inference-Time Optimization for LLM Agents

  Heng Zhou, Zelin Tan, Zhemeng Zhang, Yutao Fan, Yibing Lin · Apr 8, 2026 · Citations: 0

  Automatic Metrics General

  When an LLM-based agent improves on a task, is the gain from the model itself or from the reasoning paradigm wrapped around it?

• PEEM: Prompt Engineering Evaluation Metrics for Interpretable Joint Evaluation of Prompts and Responses

  Minki Hong, Eunsoo Lee, Sohyun Park, Jihie Kim · Mar 11, 2026 · Citations: 0

  Automatic Metrics Medicine

  We propose PEEM (Prompt Engineering Evaluation Metrics), a unified framework for joint and interpretable evaluation of both prompts and responses.

• SQLStructEval: Structural Evaluation of LLM Text-to-SQL Generation

  Yixi Zhou, Fan Zhang, Zhiqiao Guo, Yu Chen, Haipeng Zhang · Apr 8, 2026 · Citations: 0

  Automatic Metrics Coding

  Despite strong performance on Text-to-SQL benchmarks, it remains unclear whether LLM-generated SQL programs are structurally reliable.

• Adaptive Prompt Structure Factorization: A Framework for Self-Discovering and Optimizing Compositional Prompt Programs

  Haoyue Liu, Zhichao Wang, Yongxin Guo, Haoran Shou, Xiaoying Tang · Apr 8, 2026 · Citations: 0

  Automatic Metrics General

  Across multiple advanced reasoning benchmarks, aPSF outperforms strong baselines including principle-aware optimizers, improving accuracy by up to +2.16 percentage points on average, and reduces optimization cost by 45--87% tokens on…

• A Graph-Enhanced Defense Framework for Explainable Fake News Detection with LLM

  Bo Wang, Jing Ma, Hongzhan Lin, Zhiwei Yang, Ruichao Yang · Apr 8, 2026 · Citations: 0

  Automatic Metrics General

  Explainable fake news detection aims to assess the veracity of news claims while providing human-friendly explanations.

• Feedback Adaptation for Retrieval-Augmented Generation

  Jihwan Bang, Seunghan Yang, Kyuhong Shim, Simyung Chang, Juntae Lee · Apr 8, 2026 · Citations: 0

  Automatic Metrics General

  Existing evaluation protocols focus on overall accuracy and fail to capture how systems adapt after feedback is introduced.

• SHAPE: Stage-aware Hierarchical Advantage via Potential Estimation for LLM Reasoning

  Zhengyang Ai, Zikang Shan, Xiaodong Ai, Jingxian Tang, Hangkai Hu · Apr 8, 2026 · Citations: 0

  Automatic Metrics Math

  Extensive experiments in math reasoning across three base models and five benchmarks demonstrate that SHAPE achieves an average accuracy gain of 3% with 30% reduced token consumption.

• DiffuMask: Diffusion Language Model for Token-level Prompt Pruning

  Caleb Zheng, Jyotika Singh, Fang Tu, Weiyi Sun, Sujeeth Bharadwaj · Apr 8, 2026 · Citations: 0

  Automatic Metrics General

  Abstract shows limited direct human-feedback or evaluation-protocol detail; use as adjacent methodological context.

• Scientific Knowledge-driven Decoding Constraints Improving the Reliability of LLMs

  Maotian Ma, Zheni Zeng, Zhenghao Liu, Yukun Yan · Apr 8, 2026 · Citations: 0

  Automatic Metrics MedicineCoding

  Though scientific theories and rules can efficiently direct the behaviors of human manipulators, LLMs still do not utilize these highly-condensed knowledge sufficiently through training or prompting.

• Does a Global Perspective Help Prune Sparse MoEs Elegantly?

  Zeliang Zhang, Nikhil Ghosh, Jiani Liu, Bin Yu, Xiaodong Liu · Apr 8, 2026 · Citations: 0

  Automatic Metrics Law

  Abstract shows limited direct human-feedback or evaluation-protocol detail; use as adjacent methodological context.

• PACIFIC: Can LLMs Discern the Traits Influencing Your Preferences? Evaluating Personality-Driven Preference Alignment in LLMs

  Tianyu Zhao, Siqi Li, Yasser Shoukry, Salma Elmalaki · Feb 6, 2026 · Citations: 0

  Automatic Metrics General

  Based on these findings, we introduce PACIFIC (Preference Alignment Choices Inference for Five-factor Identity Characterization), a personality-labeled preference dataset containing 1200 preference statements spanning diverse domains (e.g.,…

• ValueGround: Evaluating Culture-Conditioned Visual Value Grounding in MLLMs

  Zhipin Wang, Christoph Leiter, Christian Frey, Mohamed Hesham Ibrahim Abdalla, Josif Grabocka · Apr 7, 2026 · Citations: 0

  Automatic Metrics General

  Yet existing evaluations of cultural values in language models are almost entirely text-only, making it unclear whether models can ground culture-conditioned judgments when response options are visualized.

• Multi-objective Evolutionary Merging Enables Efficient Reasoning Models

  Mario Iacobelli, Adrian Robert Minut, Tommaso Mencattini, Donato Crisostomi, Andrea Santilli · Apr 7, 2026 · Citations: 0

  Automatic Metrics Math

  Comprehensive experiments across 1.5B, 7B, and 14B parameter scales on six mathematical reasoning benchmarks demonstrate that Evo-L2S can reduce the length of generated reasoning traces by over 50% while preserving, or even improving, the…

• Context-Aware Dialectal Arabic Machine Translation with Interactive Region and Register Selection

  Afroza Nowshin, Prithweeraj Acharjee Porag, Haziq Jeelani, Fayeq Jeelani Syed · Apr 7, 2026 · Citations: 0

  Automatic Metrics Multilingual

  Through a combination of automatic evaluation and qualitative analysis, we observe an apparent accuracy-fidelity trade-off: high-resource baselines such as NLLB (No Language Left Behind) achieve higher aggregate BLEU scores (13.75) by…

• Team Fusion@ SU@ BC8 SympTEMIST track: transformer-based approach for symptom recognition and linking

  Georgi Grazhdanski, Sylvia Vassileva, Ivan Koychev, Svetla Boytcheva · Apr 7, 2026 · Citations: 0

  Automatic Metrics Multilingual

  Abstract shows limited direct human-feedback or evaluation-protocol detail; use as adjacent methodological context.

• Application-Driven Pedagogical Knowledge Optimization of Open-Source LLMs via Reinforcement Learning and Supervised Fine-Tuning

  Navan Preet Singh, Xiaokun Wang, Anurag Garikipati, Madalina Ciobanu, Qingqing Mao · Apr 7, 2026 · Citations: 0

  Automatic Metrics General

  These models remarkably achieve high enough accuracy on the Cross-Domain Pedagogical Knowledge (CDPK) Benchmark to establish new state-of-the-art (SOTA) results across the interactive Pedagogy Benchmark Leaderboard and surpass significantly…

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