- AgentHER: Hindsight Experience Replay for LLM Agent Trajectory Relabeling
Liang Ding · Mar 22, 2026 · Citations: 0
Demonstrations Human EvalLlm As Judge Long Horizon
LLM agents fail on the majority of real-world tasks -- GPT-4o succeeds on fewer than 15% of WebArena navigation tasks and below 55% pass@1 on ToolBench (Zhou et al., 2024; Qin et al., 2024) -- yet every failed trajectory is routinely…
- LMUnit: Fine-grained Evaluation with Natural Language Unit Tests
Jon Saad-Falcon, Rajan Vivek, William Berrios, Nandita Shankar Naik, Matija Franklin · Dec 17, 2024 · Citations: 0
Pairwise Preference Human Eval
We introduce natural language unit tests, a paradigm that decomposes response quality into explicit, testable criteria, along with a unified scoring model, LMUnit, which combines multi-objective training across preferences, direct ratings,…
- PoSh: Using Scene Graphs To Guide LLMs-as-a-Judge For Detailed Image Descriptions
Amith Ananthram, Elias Stengel-Eskin, Lorena A. Bradford, Julia Demarest, Adam Purvis · Oct 21, 2025 · Citations: 0
Rubric Rating Human EvalLlm As Judge
In this work, we introduce PoSh, a metric for detailed image description that uses scene graphs as structured rubrics to guide LLMs-as-a-Judge, producing aggregate scores grounded in fine-grained errors (e.g.
- Validating Political Position Predictions of Arguments
Jordan Robinson, Angus R. Williams, Katie Atkinson, Anthony G. Cohn · Feb 20, 2026 · Citations: 0
Pairwise Preference Human Eval
Real-world knowledge representation often requires capturing subjective, continuous attributes -- such as political positions -- that conflict with pairwise validation, the widely accepted gold standard for human evaluation.
- LLM Essay Scoring Under Holistic and Analytic Rubrics: Prompt Effects and Bias
Filip J. Kucia, Anirban Chakraborty, Anna Wróblewska · Mar 31, 2026 · Citations: 0
Rubric Rating Human Eval
We present a systematic evaluation of instruction-tuned LLMs across three open essay-scoring datasets (ASAP 2.0, ELLIPSE, and DREsS) that cover both holistic and analytic scoring.
- SCOPE: Selective Conformal Optimized Pairwise LLM Judging
Sher Badshah, Ali Emami, Hassan Sajjad · Feb 13, 2026 · Citations: 0
Pairwise Preference Automatic Metrics
Large language models (LLMs) are increasingly used as judges to replace costly human preference labels in pairwise evaluation.
- Personalized RewardBench: Evaluating Reward Models with Human Aligned Personalization
Qiyao Ma, Dechen Gao, Rui Cai, Boqi Zhao, Hanchu Zhou · Apr 8, 2026 · Citations: 0
Pairwise PreferenceRubric Rating Human EvalAutomatic Metrics
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.
- No Free Labels: Limitations of LLM-as-a-Judge Without Human Grounding
Michael Krumdick, Charles Lovering, Varshini Reddy, Seth Ebner, Chris Tanner · Mar 7, 2025 · Citations: 0
Pairwise Preference Llm As Judge
To address this gap, we introduce the Business and Finance Fundamentals Benchmark (BFF-Bench), a dataset of 160 challenging questions and long-form responses authored by financial professionals.
- 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
Red Team Automatic Metrics Long Horizon
As large language models (LLMs) evolve from static chatbots into autonomous agents, the primary vulnerability surface shifts from final outputs to intermediate execution traces.
- SODIUM: From Open Web Data to Queryable Databases
Chuxuan Hu, Philip Li, Maxwell Yang, Daniel Kang · Mar 19, 2026 · Citations: 0
Expert Verification Automatic Metrics Multi Agent
Existing systems struggle with SODIUM tasks: we evaluate 6 advanced AI agents on SODIUM-Bench, with the strongest baseline achieving only 46.5% accuracy.
- Elo-Evolve: A Co-evolutionary Framework for Language Model Alignment
Jing Zhao, Ting Zhen, Junwei Bao, Hongfei Jiang, Yang Song · Feb 14, 2026 · Citations: 0
Pairwise Preference Automatic Metrics Multi Agent
Current alignment methods for Large Language Models (LLMs) rely on compressing vast amounts of human preference data into static, absolute reward functions, leading to data scarcity, noise sensitivity, and training instability.
- PEARL: Self-Evolving Assistant for Time Management with Reinforcement Learning
Bingxuan Li, Jeonghwan Kim, Cheng Qian, Xiusi Chen, Eitan Anzenberg · Jan 17, 2026 · Citations: 0
Pairwise Preference Automatic Metrics Long Horizon
To enable a systematic study of this question, we introduce CalConflictBench, a benchmark for long-horizon calendar conflict resolution.
- More Human, More Efficient: Aligning Annotations with Quantized SLMs
Jiayu Wang, Junyoung Lee · Apr 1, 2026 · Citations: 0
Rubric Rating Automatic Metrics
As Large Language Model (LLM) capabilities advance, the demand for high-quality annotation of exponentially increasing text corpora has outpaced human capacity, leading to the widespread adoption of LLMs in automatic evaluation and…
- From Intuition to Calibrated Judgment: A Rubric-Based Expert-Panel Study of Human Detection of LLM-Generated Korean Text
Shinwoo Park, Yo-Sub Han · Jan 6, 2026 · Citations: 0
Rubric Rating Automatic Metrics
Distinguishing human-written Korean text from fluent LLM outputs remains difficult even for trained readers, who can over-trust surface well-formedness.
- Beyond the Illusion of Consensus: From Surface Heuristics to Knowledge-Grounded Evaluation in LLM-as-a-Judge
Mingyang Song, Mao Zheng, Chenning Xu · Mar 11, 2026 · Citations: 0
Rubric RatingCritique Edit Llm As Judge
Through a large-scale study of 105,600 evaluation instances (32 LLMs \times 3 frontier judges \times 100 tasks \times 11 temperatures), we show that model-level agreement (Spearman ρ= 0.99) masks fragile sample-level agreement (Pearson r =…
- Evaluating Austrian A-Level German Essays with Large Language Models for Automated Essay Scoring
Jonas Kubesch, Lena Huber, Clemens Havas · Mar 6, 2026 · Citations: 0
Rubric Rating Human Eval
This paper investigates the application of state-of-the-art open-weight LLMs for the grading of Austrian A-level German texts, with a particular focus on rubric-based evaluation.
- Meanings and Measurements: Multi-Agent Probabilistic Grounding for Vision-Language Navigation
Swagat Padhan, Lakshya Jain, Bhavya Minesh Shah, Omkar Patil, Thao Nguyen · Mar 19, 2026 · Citations: 0
Demonstrations Simulation Env Multi Agent
To address this limitation, we propose MAPG (Multi-Agent Probabilistic Grounding), an agentic framework that decomposes language queries into structured subcomponents and queries a VLM to ground each component.
- LifeSim: Long-Horizon User Life Simulator for Personalized Assistant Evaluation
Feiyu Duan, Xuanjing Huang, Zhongyu Wei · Mar 12, 2026 · Citations: 0
Pairwise Preference Simulation Env Long Horizon
However, existing benchmarks for personalized assistants remain misaligned with real-world user-assistant interactions, failing to capture the complexity of external contexts and users' cognitive states.
- Beyond Paper-to-Paper: Structured Profiling and Rubric Scoring for Paper-Reviewer Matching
Yicheng Pan, Zhiyuan Ning, Ludi Wang, Yi Du · Apr 7, 2026 · Citations: 0
Rubric Rating Automatic Metrics
To address this gap, we propose P2R, a training-free framework that shifts from implicit paper-to-paper matching to explicit profile-based matching.
- When AI Meets Early Childhood Education: Large Language Models as Assessment Teammates in Chinese Preschools
Xingming Li, Runke Huang, Yanan Bao, Yuye Jin, Yuru Jiao · Mar 25, 2026 · Citations: 0
Rubric Rating Automatic Metrics
In this paper, we investigate whether AI can serve as a scalable assessment teammate by extracting structured quality indicators and validating their alignment with human expert judgments.
- A Coin Flip for Safety: LLM Judges Fail to Reliably Measure Adversarial Robustness
Leo Schwinn, Moritz Ladenburger, Tim Beyer, Mehrnaz Mofakhami, Gauthier Gidel · Feb 4, 2026 · Citations: 0
Red Team Llm As Judge
Automated LLM-as-a-Judge frameworks have become the de facto standard for scalable evaluation across natural language processing.
- MemoryArena: Benchmarking Agent Memory in Interdependent Multi-Session Agentic Tasks
Zexue He, Yu Wang, Churan Zhi, Yuanzhe Hu, Tzu-Ping Chen · Feb 18, 2026 · Citations: 0
Pairwise Preference Automatic Metrics Web Browsing
Existing evaluations of agents with memory typically assess memorization and action in isolation.
- RedTeamCUA: Realistic Adversarial Testing of Computer-Use Agents in Hybrid Web-OS Environments
Zeyi Liao, Jaylen Jones, Linxi Jiang, Yuting Ning, Eric Fosler-Lussier · May 28, 2025 · Citations: 0
Red Team Automatic Metrics Web Browsing
Using RedTeamCUA, we develop RTC-Bench, a comprehensive benchmark with 864 examples that investigate realistic, hybrid web-OS attack scenarios and fundamental security vulnerabilities.
- SOLE-R1: Video-Language Reasoning as the Sole Reward for On-Robot Reinforcement Learning
Philip Schroeder, Thomas Weng, Karl Schmeckpeper, Eric Rosen, Stephen Hart · Mar 30, 2026 · Citations: 0
Demonstrations Simulation Env Long Horizon
To address this limitation, we introduce SOLE-R1 (Self-Observing LEarner), a video-language reasoning model explicitly designed to serve as the sole reward signal for online RL.
- Build, Judge, Optimize: A Blueprint for Continuous Improvement of Multi-Agent Consumer Assistants
Alejandro Breen Herrera, Aayush Sheth, Steven G. Xu, Zhucheng Zhan, Charles Wright · Mar 3, 2026 · Citations: 0
Pairwise PreferenceRubric Rating Llm As JudgeSimulation Env Long Horizon
Conversational shopping assistants (CSAs) represent a compelling application of agentic AI, but moving from prototype to production reveals two underexplored challenges: how to evaluate multi-turn interactions and how to optimize tightly…
- EvolvR: Self-Evolving Pairwise Reasoning for Story Evaluation to Enhance Generation
Xinda Wang, Zhengxu Hou, Yangshijie Zhang, Bingren Yan, Jialin Liu · Aug 8, 2025 · Citations: 0
Pairwise Preference Llm As Judge Multi Agent
Although the effectiveness of Large Language Models (LLMs) as judges (LLM-as-a-judge) has been validated, their performance remains limited in open-ended tasks, particularly in story evaluation.
- IF-RewardBench: Benchmarking Judge Models for Instruction-Following Evaluation
Bosi Wen, Yilin Niu, Cunxiang Wang, Xiaoying Ling, Ying Zhang · Mar 5, 2026 · Citations: 0
Pairwise Preference Llm As Judge
Instruction-following is a foundational capability of large language models (LLMs), with its improvement hinging on scalable and accurate feedback from judge models.
- EditReward: A Human-Aligned Reward Model for Instruction-Guided Image Editing
Keming Wu, Sicong Jiang, Max Ku, Ping Nie, Minghao Liu · Sep 30, 2025 · Citations: 0
Pairwise Preference Llm As Judge
To address this critical bottleneck, we built EditReward, trained with our new large-scale human preference dataset, meticulously annotated by trained experts following a rigorous protocol containing over 200K preference pairs.
- From Consensus to Split Decisions: ABC-Stratified Sentiment in Holocaust Oral Histories
Daban Q. Jaff · Mar 30, 2026 · Citations: 0
Pairwise Preference Automatic Metrics
After assembling model outputs, we introduce an agreement-based stability taxonomy (ABC) to stratify inter-model output stability.
- Measuring Faithfulness Depends on How You Measure: Classifier Sensitivity in LLM Chain-of-Thought Evaluation
Richard J. Young · Mar 20, 2026 · Citations: 0
Pairwise Preference Automatic Metrics
Three classifiers (a regex-only detector, a regex-plus-LLM pipeline, and a Claude Sonnet 4 judge) are applied to 10,276 influenced reasoning traces from 12 open-weight models spanning 9 families and 7B to 1T parameters.
- Personalized Prediction of Perceived Message Effectiveness Using Large Language Model Based Digital Twins
Jasmin Han, Janardan Devkota, Joseph Waring, Amanda Luken, Felix Naughton · Feb 23, 2026 · Citations: 0
Rubric Rating Automatic Metrics
Model performance was assessed on three held-out messages per participant using accuracy, Cohen's kappa, and F1.
- Yor-Sarc: A gold-standard dataset for sarcasm detection in a low-resource African language
Toheeb Aduramomi Jimoh, Tabea De Wille, Nikola S. Nikolov · Feb 21, 2026 · Citations: 0
Pairwise Preference Automatic Metrics
This protocol incorporates context-sensitive interpretation and community-informed guidelines and is accompanied by a comprehensive analysis of inter-annotator agreement to support replication in other African languages.
- InnoEval: On Research Idea Evaluation as a Knowledge-Grounded, Multi-Perspective Reasoning Problem
Shuofei Qiao, Yunxiang Wei, Xuehai Wang, Bin Wu, Boyang Xue · Feb 16, 2026 · Citations: 0
Llm As Judge Web Browsing
The rapid evolution of Large Language Models has catalyzed a surge in scientific idea production, yet this leap has not been accompanied by a matching advance in idea evaluation.
- Toward Safe and Human-Aligned Game Conversational Recommendation via Multi-Agent Decomposition
Zheng Hui, Xiaokai Wei, Yexi Jiang, Kevin Gao, Chen Wang · Apr 26, 2025 · Citations: 0
Pairwise Preference Automatic Metrics Multi Agent
These domains typically involve fixed content and passive consumption, where user preferences can be matched by genre or theme.
- PONTE: Personalized Orchestration for Natural Language Trustworthy Explanations
Vittoria Vineis, Matteo Silvestri, Lorenzo Antonelli, Filippo Betello, Gabriele Tolomei · Mar 6, 2026 · Citations: 0
Pairwise Preference Human Eval
To address these challenges, we present PONTE (Personalized Orchestration for Natural language Trustworthy Explanations), a human-in-the-loop framework for adaptive and reliable XAI narratives.
- VRM: Teaching Reward Models to Understand Authentic Human Preferences
Biao Liu, Ning Xu, Junming Yang, Hao Xu, Xin Geng · Mar 5, 2026 · Citations: 0
Pairwise Preference Human Eval
Large Language Models (LLMs) have achieved remarkable success across diverse natural language tasks, yet the reward models employed for aligning LLMs often encounter challenges of reward hacking, where the approaches predominantly rely on…
- HEART: A Unified Benchmark for Assessing Humans and LLMs in Emotional Support Dialogue
Laya Iyer, Kriti Aggarwal, Sanmi Koyejo, Gail Heyman, Desmond C. Ong · Jan 9, 2026 · Citations: 0
Pairwise PreferenceRubric Rating Human EvalLlm As Judge
Despite rapid progress in language models, we still lack a clear way to understand how their abilities in these interpersonal domains compare to those of humans.
- Signals: Trajectory Sampling and Triage for Agentic Interactions
Shuguang Chen, Adil Hafeez, Salman Paracha · Apr 1, 2026 · Citations: 0
Pairwise Preference Automatic Metrics Long Horizon
We propose a lightweight, signal-based framework for triaging agentic interaction trajectories.
- The Geometry of Dialogue: Graphing Language Models to Reveal Synergistic Teams for Multi-Agent Collaboration
Kotaro Furuya, Yuichi Kitagawa · Oct 30, 2025 · Citations: 0
Pairwise Preference Automatic Metrics Multi Agent
While a multi-agent approach based on large language models (LLMs) represents a promising strategy to surpass the capabilities of single models, its success is critically dependent on synergistic team composition.
- Rethinking Atomic Decomposition for LLM Judges: A Prompt-Controlled Study of Reference-Grounded QA Evaluation
Xinran Zhang · Mar 30, 2026 · Citations: 0
Rubric Rating Automatic Metrics
Atomic decomposition -- breaking a candidate answer into claims before verifying each against a reference -- is a widely adopted design for LLM-based reference-grounded judges.
- SemEval-2026 Task 6: CLARITY -- Unmasking Political Question Evasions
Konstantinos Thomas, Giorgos Filandrianos, Maria Lymperaiou, Chrysoula Zerva, Giorgos Stamou · Mar 14, 2026 · Citations: 0
Red Team Automatic Metrics
The benchmark is constructed from U.S.
- Beyond Rows to Reasoning: Agentic Retrieval for Multimodal Spreadsheet Understanding and Editing
Anmol Gulati, Sahil Sen, Waqar Sarguroh, Kevin Paul · Mar 6, 2026 · Citations: 0
Human EvalAutomatic Metrics Long Horizon
We introduce Beyond Rows to Reasoning (BRTR), a multimodal agentic framework for spreadsheet understanding that replaces single-pass retrieval with an iterative tool-calling loop, supporting end-to-end Excel workflows from complex analysis…
- How Reliable is Language Model Micro-Benchmarking?
Gregory Yauney, Shahzaib Saqib Warraich, Swabha Swayamdipta · Oct 9, 2025 · Citations: 0
Pairwise Preference Automatic Metrics
We introduce a meta-evaluation measure for micro-benchmarking which investigates how well a micro-benchmark can rank two models as a function of their performance difference on the full benchmark.
- ReDAct: Uncertainty-Aware Deferral for LLM Agents
Dzianis Piatrashyn, Nikita Kotelevskii, Kirill Grishchenkov, Nikita Glazkov, Ivan Nasonov · Apr 8, 2026 · Citations: 0
Simulation Env Long Horizon
Recently, LLM-based agents have become increasingly popular across many applications, including complex sequential decision-making problems.
- Deep Research, Shallow Evaluation: A Case Study in Meta-Evaluation for Long-Form QA Benchmarks
Jena D. Hwang, Varsha Kishore, Amanpreet Singh, Dany Haddad, Aakanksha Naik · Mar 6, 2026 · Citations: 0
Pairwise PreferenceExpert Verification Llm As Judge
This has prompted evaluation frameworks that use LLM-as-judge protocols and claim verification, along with meta-evaluation frameworks that seek to validate these methods.
- Embodied Task Planning via Graph-Informed Action Generation with Large Language Model
Xiang Li, Ning Yan, Masood Mortazavi · Jan 29, 2026 · Citations: 0
Simulation Env Long Horizon
We propose GiG, a novel planning framework that structures embodied agents' memory using a Graph-in-Graph architecture.
- Go-Browse: Training Web Agents with Structured Exploration
Apurva Gandhi, Graham Neubig · Jun 4, 2025 · Citations: 0
Simulation Env Web Browsing
To address this, we propose Go-Browse, a method for automatically collecting diverse and realistic web agent data at scale through structured exploration of web environments.
- From Control to Foresight: Simulation as a New Paradigm for Human-Agent Collaboration
Gaole He, Brian Y. Lim · Mar 12, 2026 · Citations: 0
Pairwise Preference Simulation Env Long Horizon
Large Language Models (LLMs) are increasingly used to power autonomous agents for complex, multi-step tasks.
- Dual-Modality Multi-Stage Adversarial Safety Training: Robustifying Multimodal Web Agents Against Cross-Modal Attacks
Haoyu Liu, Dingcheng Li, Lukas Rutishauser, Zeyu Zheng · Mar 4, 2026 · Citations: 0
Demonstrations Simulation Env
Multimodal web agents that process both screenshots and accessibility trees are increasingly deployed to interact with web interfaces, yet their dual-stream architecture opens an underexplored attack surface: an adversary who injects…
- RebuttalAgent: Strategic Persuasion in Academic Rebuttal via Theory of Mind
Zhitao He, Zongwei Lyu, Yi R Fung · Jan 22, 2026 · Citations: 0
Pairwise PreferenceCritique Edit Human Eval
In this paper, we introduce RebuttalAgent, the first framework to ground academic rebuttal in Theory of Mind (ToM), operationalized through a ToM-Strategy-Response (TSR) framework that models reviewer mental state, formulates persuasion…
- Refusal Steering: Fine-grained Control over LLM Refusal Behaviour for Sensitive Topics
Iker García-Ferrero, David Montero, Roman Orus · Dec 18, 2025 · Citations: 0
Red Team Llm As Judge
We replace fragile pattern-based refusal detection with an LLM-as-a-judge that assigns refusal confidence scores and we propose a ridge-regularized variant to compute steering vectors that better isolate the refusal--compliance direction.
- DSPO: Stable and Efficient Policy Optimization for Agentic Search and Reasoning
Chenyang Gu, Yewen Pu, Bruce Yang, Xiaofan Li, Huan Gao · Oct 10, 2025 · Citations: 0
Demonstrations Simulation Env
Current approaches either rely on prompting to elicit the model's innate agent capabilities, or suffer from performance ceilings and collapse when applying RL to complex interactive tasks, leaving their true agentic potential untapped.
- Structured Agent Distillation for Large Language Model
Jun Liu, Zhenglun Kong, Peiyan Dong, Changdi Yang, Tianqi Li · May 20, 2025 · Citations: 0
Demonstrations Simulation Env
Large language models (LLMs) exhibit strong capabilities as decision-making agents by interleaving reasoning and actions, as seen in ReAct-style frameworks.
- ReasonScaffold: A Scaffolded Reasoning-based Annotation Protocol for Human-AI Co-Annotation
Smitha Muthya Sudheendra, Jaideep Srivastava · Mar 22, 2026 · Citations: 0
Critique Edit Automatic Metrics
We evaluate the approach on sentiment classification and opinion detection tasks, analyzing changes in inter-annotator agreement and revision behavior.
- IA2: Alignment with ICL Activations Improves Supervised Fine-Tuning
Aayush Mishra, Daniel Khashabi, Anqi Liu · Sep 26, 2025 · Citations: 0
Demonstrations Automatic Metrics
Performing IA2 as a priming step before SFT significantly improves the accuracy and calibration of model outputs, as shown by our extensive empirical results on 12 popular benchmarks and two model families.
- 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
Expert Verification Automatic Metrics
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…
- Aligning Multimodal Sequential Recommendations via Robust Direct Preference Optimization with Sparse MoE
Hejin Huang, Jusheng Zhang, Kaitong Cai, Jian Wang, Rong Pan · Mar 31, 2026 · Citations: 0
Pairwise Preference Automatic Metrics
Preference-based alignment objectives have been widely adopted, from RLHF-style pairwise learning in large language models to emerging applications in recommender systems.
- Prompt Attack Detection with LLM-as-a-Judge and Mixture-of-Models
Hieu Xuan Le, Benjamin Goh, Quy Anh Tang · Mar 26, 2026 · Citations: 0
Red Team Llm As Judge
In production, guardrails must mitigate these attacks under strict low-latency constraints, resulting in a deployment gap in which lightweight classifiers and rule-based systems struggle to generalize under distribution shift, while…
- Red-Teaming Vision-Language-Action Models via Quality Diversity Prompt Generation for Robust Robot Policies
Siddharth Srikanth, Freddie Liang, Ya-Chuan Hsu, Varun Bhatt, Shihan Zhao · Mar 12, 2026 · Citations: 0
Red Team Simulation Env
Our results across multiple simulation benchmarks show that Q-DIG finds more diverse and meaningful failure modes compared to baseline methods, and that fine-tuning VLAs on the generated instructions improves task success rates.
- CHiL(L)Grader: Calibrated Human-in-the-Loop Short-Answer Grading
Pranav Raikote, Korbinian Randl, Ioanna Miliou, Athanasios Lakes, Panagiotis Papapetrou · Mar 12, 2026 · Citations: 0
Rubric Rating Automatic Metrics
We introduce CHiL(L)Grader, the first automated grading framework that incorporates calibrated confidence estimation into a human-in-the-loop workflow.