- 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.
- PubMed Reasoner: Dynamic Reasoning-based Retrieval for Evidence-Grounded Biomedical Question Answering
Yiqing Zhang, Xiaozhong Liu, Fabricio Murai · Mar 28, 2026 · Citations: 0
Expert Verification Llm As JudgeAutomatic Metrics
In this context, we introduce PubMed Reasoner, a biomedical QA agent composed of three stages: self-critic query refinement evaluates MeSH terms for coverage, alignment, and redundancy to enhance PubMed queries based on partial (metadata)…
- Improving Clinical Diagnosis with Counterfactual Multi-Agent Reasoning
Zhiwen You, Xi Chen, Aniket Vashishtha, Simo Du, Gabriel Erion-Barner · Mar 29, 2026 · Citations: 0
Expert Verification Human EvalAutomatic Metrics Multi Agent
In this work, we propose a counterfactual multi-agent diagnostic framework inspired by clinician training that makes hypothesis testing explicit and evidence-grounded.
- 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.
- 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…
- Blinded Radiologist and LLM-Based Evaluation of LLM-Generated Japanese Translations of Chest CT Reports: Comparative Study
Yosuke Yamagishi, Atsushi Takamatsu, Yasunori Hamaguchi, Tomohiro Kikuchi, Shouhei Hanaoka · Apr 2, 2026 · Citations: 0
Pairwise Preference Llm As JudgeAutomatic Metrics
A board-certified radiologist and a radiology resident independently performed blinded pairwise evaluations across 4 criteria: terminology accuracy, readability, overall quality, and radiologist-style authenticity.
- PRBench: End-to-end Paper Reproduction in Physics Research
Shi Qiu, Junyi Deng, Yiwei Deng, Haoran Dong, Jieyu Fu · Mar 29, 2026 · Citations: 0
Rubric RatingExpert Verification Automatic MetricsSimulation Env
We introduce PRBench, a benchmark of 30 expert-curated tasks spanning 11 subfields of physics.
- Step-CoT: Stepwise Visual Chain-of-Thought for Medical Visual Question Answering
Lin Fan, Yafei Ou, Zhipeng Deng, Pengyu Dai, Hou Chongxian · Mar 14, 2026 · Citations: 0
Expert Verification Automatic Metrics Long Horizon
Benchmark: github.com/hahaha111111/Step-CoT.
- 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.
- Xpertbench: Expert Level Tasks with Rubrics-Based Evaluation
Xue Liu, Xin Ma, Yuxin Ma, Yongchang Peng, Duo Wang · Mar 27, 2026 · Citations: 0
Rubric RatingExpert Verification Automatic Metrics
To bridge this gap, we present XpertBench, a high-fidelity benchmark engineered to assess LLMs across authentic professional domains.
- 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.
- QuarkMedBench: A Real-World Scenario Driven Benchmark for Evaluating Large Language Models
Yao Wu, Kangping Yin, Liang Dong, Zhenxin Ma, Shuting Xu · Mar 14, 2026 · Citations: 0
Rubric Rating Automatic Metrics
To bridge this gap, we introduce QuarkMedBench, an ecologically valid benchmark tailored for real-world medical LLM assessment.
- A Multi-Stage Validation Framework for Trustworthy Large-scale Clinical Information Extraction using Large Language Models
Maria Mahbub, Gregory M. Dams, Josh Arnold, Caitlin Rizy, Sudarshan Srinivasan · Apr 7, 2026 · Citations: 0
Expert Verification Automatic Metrics
Conventional evaluation methods rely heavily on annotation-intensive reference standards or incomplete structured data, limiting feasibility at population scale.
- 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.
- Automating Clinical Information Retrieval from Finnish Electronic Health Records Using Large Language Models
Mikko Saukkoriipi, Nicole Hernandez, Jaakko Sahlsten, Kimmo Kaski, Otso Arponen · Mar 27, 2026 · Citations: 0
Expert Verification Automatic Metrics
Open-source large language models (LLMs) ranging from 4B to 70B parameters were benchmarked under fully offline conditions using 1,664 expert-annotated question-answer pairs derived from records of 183 patients.
- SleepVLM: Explainable and Rule-Grounded Sleep Staging via a Vision-Language Model
Guifeng Deng, Pan Wang, Jiquan Wang, Shuying Rao, Junyi Xie · Mar 22, 2026 · Citations: 0
Expert Verification Automatic Metrics
Expert evaluations further validated the quality of the model's reasoning, with mean scores exceeding 4.0/5.0 for factual accuracy, evidence comprehensiveness, and logical coherence.
- 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.
- HyperMem: Hypergraph Memory for Long-Term Conversations
Juwei Yue, Chuanrui Hu, Jiawei Sheng, Zuyi Zhou, Wenyuan Zhang · Apr 9, 2026 · Citations: 0
Pairwise Preference Llm As JudgeAutomatic Metrics
Long-term memory is essential for conversational agents to maintain coherence, track persistent tasks, and provide personalized interactions across extended dialogues.
- RuleForge: Automated Generation and Validation for Web Vulnerability Detection at Scale
Ayush Garg, Sophia Hager, Jacob Montiel, Aditya Tiwari, Michael Gentile · Apr 2, 2026 · Citations: 0
Expert Verification Llm As JudgeAutomatic Metrics
This paper focuses on RuleForge's architecture and operational deployment for CVE-related threat detection, with particular emphasis on our novel LLM-as-a-judge (Large Language Model as judge) confidence validation system and systematic…
- 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.
- ClinicalAgents: Multi-Agent Orchestration for Clinical Decision Making with Dual-Memory
Zhuohan Ge, Haoyang Li, Yubo Wang, Nicole Hu, Chen Jason Zhang · Mar 27, 2026 · Citations: 0
Expert Verification Automatic Metrics Multi Agent
To bridge this gap, we introduce ClinicalAgents, a novel multi-agent framework designed to simulate the cognitive workflow of expert clinicians.
- Learning When to Act: Interval-Aware Reinforcement Learning with Predictive Temporal Structure
Davide Di Gioia · Mar 23, 2026 · Citations: 0
Pairwise Preference Automatic Metrics Long Horizon
Autonomous agents operating in continuous environments must decide not only what to do, but when to act.
- A Multidisciplinary AI Board for Multimodal Dementia Characterization and Risk Assessment
Sheng Liu, Long Chen, Zeyun Zhao, Qinglin Gou, Qingyue Wei · Mar 23, 2026 · Citations: 0
Expert Verification Automatic Metrics Multi Agent
We present Cerebra, an interactive multi-agent AI team that coordinates specialized agents for EHR, clinical notes, and medical imaging analysis.
- Paper Reconstruction Evaluation: Evaluating Presentation and Hallucination in AI-written Papers
Atsuyuki Miyai, Mashiro Toyooka, Zaiying Zhao, Kenta Watanabe, Toshihiko Yamasaki · Apr 1, 2026 · Citations: 0
Rubric Rating Automatic Metrics
We introduce Paper Reconstruction Evaluation (PaperRecon), an evaluation framework in which an overview (overview.md) is created from an existing paper, after which an agent generates a full paper based on the overview and minimal…
- 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.
- Stabilizing Rubric Integration Training via Decoupled Advantage Normalization
Zelin Tan, Zhouliang Yu, Bohan Lin, Zijie Geng, Hejia Geng · Mar 27, 2026 · Citations: 0
Rubric Rating Automatic Metrics
We propose Process-Aware Policy Optimization (PAPO), a method that integrates process-level evaluation into Group Relative Policy Optimization (GRPO) through decoupled advantage normalization, to address two limitations of existing reward…
- FairMed-XGB: A Bayesian-Optimised Multi-Metric Framework with Explainability for Demographic Equity in Critical Healthcare Data
Mitul Goswami, Romit Chatterjee, Arif Ahmed Sekh · Mar 16, 2026 · Citations: 0
Expert Verification Automatic Metrics
Post-mitigation evaluation on seven clinically distinct cohorts derived from the MIMIC-IV-ED and eICU databases demonstrates substantial bias reduction: Statistical Parity Difference decreases by 40 to 51 percent on MIMIC-IV-ED and 10 to 19…
- Modeling and Benchmarking Spoken Dialogue Rewards with Modality and Colloquialness
Jingyu Lu, Yuhan Wang, Fan Zhuo, Xize Cheng, Changhao Pan · Mar 16, 2026 · Citations: 0
Pairwise Preference Automatic Metrics
To address these challenges, we introduce SDiaReward, an end-to-end multi-turn reward model trained on SDiaReward-Dataset, a novel collection of episode-level preference pairs explicitly targeting these gaps.
- 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.
- Entropy trajectory shape predicts LLM reasoning reliability: A diagnostic study of uncertainty dynamics in chain-of-thought
Xinghao Zhao · Mar 19, 2026 · Citations: 0
Automatic Metrics Long Horizon
Chain-of-thought (CoT) reasoning improves LLM accuracy, yet detecting failures cheaply remains elusive.
- 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.
- 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.
- OMIND: Framework for Knowledge Grounded Finetuning and Multi-Turn Dialogue Benchmark for Mental Health LLMs
Suraj Racha, Prashant Harish Joshi, Utkarsh Maurya, Nitin Yadav, Mridul Sharma · Mar 26, 2026 · Citations: 0
Rubric Rating Automatic Metrics
We highlight three primary challenges for LLMs in mental health - lack of high quality interpretable and knowledge grounded training data; training paradigms restricted to core capabilities, and evaluation of multi turn dialogue settings.
- Do Phone-Use Agents Respect Your Privacy?
Zhengyang Tang, Ke Ji, Xidong Wang, Zihan Ye, Xinyuan Wang · Apr 1, 2026 · Citations: 0
Pairwise Preference Automatic Metrics
We study whether phone-use agents respect privacy while completing benign mobile tasks.
- ClimateCheck 2026: Scientific Fact-Checking and Disinformation Narrative Classification of Climate-related Claims
Raia Abu Ahmad, Max Upravitelev, Aida Usmanova, Veronika Solopova, Georg Rehm · Mar 27, 2026 · Citations: 0
Pairwise Preference Automatic Metrics
In addition to standard evaluation metrics (Recall@K and Binary Preference), we adapt an automated framework to assess retrieval quality under incomplete annotations, exposing systematic biases in how conventional metrics rank systems.
- Stabilizing Iterative Self-Training with Verified Reasoning via Symbolic Recursive Self-Alignment
Xinyu Zhang · Mar 23, 2026 · Citations: 0
Pairwise Preference Automatic Metrics
We further demonstrate that constructing DPO preference pairs from NSRSA verification teaches the model to distinguish sound from flawed reasoning (reward accuracy 46% to 63%).
- DSPA: Dynamic SAE Steering for Data-Efficient Preference Alignment
James Wedgwood, Aashiq Muhamed, Mona T. Diab, Virginia Smith · Mar 23, 2026 · Citations: 0
Pairwise Preference Automatic Metrics
Preference alignment is usually achieved by weight-updating training on preference data, which adds substantial alignment-stage compute and provides limited mechanistic visibility.
- PAVE: Premise-Aware Validation and Editing for Retrieval-Augmented LLMs
Tianyi Huang, Caden Yang, Emily Yin, Eric Wang, Michael Zhang · Mar 21, 2026 · Citations: 0
Critique Edit Automatic Metrics
In controlled ablations with a fixed retriever and backbone, PAVE outperforms simpler post-retrieval baselines in two evidence-grounded QA settings, with the largest gain reaching 32.7 accuracy points on a span-grounded benchmark.
- CausalRM: Causal-Theoretic Reward Modeling for RLHF from Observational User Feedbacks
Hao Wang, Licheng Pan, Zhichao Chen, Chunyuan Zheng, Zhixuan Chu · Mar 19, 2026 · Citations: 0
Pairwise Preference Automatic Metrics
Despite the success of reinforcement learning from human feedback (RLHF) in aligning language models, current reward modeling heavily relies on experimental feedback data collected from human annotators under controlled and costly…
- DeceptGuard :A Constitutional Oversight Framework For Detecting Deception in LLM Agents
Snehasis Mukhopadhyay · Mar 14, 2026 · Citations: 0
Automatic MetricsSimulation Env Long Horizon
We introduce DECEPTGUARD, a unified framework that systematically compares three monitoring regimes: black-box monitors (actions and outputs only), CoT-aware monitors (additionally observing the agent's chain-of-thought reasoning trace),…
- How Much LLM Does a Self-Revising Agent Actually Need?
Sungwoo Jung, Seonil Son · Apr 8, 2026 · Citations: 0
Critique Edit Automatic Metrics
Recent LLM-based agents often place world modeling, planning, and reflection inside a single language model loop.
- 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
Expert Verification Automatic Metrics
Third, results on the development set show that alignment accuracy is mainly limited by reasoning.
- MMEmb-R1: Reasoning-Enhanced Multimodal Embedding with Pair-Aware Selection and Adaptive Control
Yuchi Wang, Haiyang Yu, Weikang Bian, Jiefeng Long, Xiao Liang · Apr 7, 2026 · Citations: 0
Pairwise Preference Automatic Metrics
Experiments on the MMEB-V2 benchmark demonstrate that our model achieves a score of 71.2 with only 4B parameters, establishing a new state-of-the-art while significantly reducing reasoning overhead and inference latency.
- Social Dynamics as Critical Vulnerabilities that Undermine Objective Decision-Making in LLM Collectives
Changgeon Ko, Jisu Shin, Hoyun Song, Huije Lee, Eui Jun Hwang · Apr 7, 2026 · Citations: 0
Automatic MetricsSimulation Env Multi Agent
Large language model (LLM) agents are increasingly acting as human delegates in multi-agent environments, where a representative agent integrates diverse peer perspectives to make a final decision.
- QED-Nano: Teaching a Tiny Model to Prove Hard Theorems
LM-Provers, Yuxiao Qu, Amrith Setlur, Jasper Dekoninck, Edward Beeching · Apr 6, 2026 · Citations: 0
Rubric Rating Automatic Metrics
To support further research on open mathematical reasoning, we release the full QED-Nano pipeline, including the QED-Nano and QED-Nano-SFT models, the FineProofs-SFT and FineProofs-RL datasets, and the training and evaluation code.
- Optimizing RAG Rerankers with LLM Feedback via Reinforcement Learning
Yuhang Wu, Xiangqing Shen, Fanfan Wang, Cangqi Zhou, Zhen Wu · Apr 2, 2026 · Citations: 0
Pairwise Preference Automatic Metrics
However, current reranking models are typically optimized on static human annotated relevance labels in isolation, decoupled from the downstream generation process.
- Development and multi-center evaluation of domain-adapted speech recognition for human-AI teaming in real-world gastrointestinal endoscopy
Ruijie Yang, Yan Zhu, Peiyao Fu, Te Luo, Zhihua Wang · Apr 2, 2026 · Citations: 0
Expert Verification Automatic Metrics
Automatic speech recognition (ASR) is a critical interface for human-AI interaction in gastrointestinal endoscopy, yet its reliability in real-world clinical settings is limited by domain-specific terminology and complex acoustic…
- Preference learning in shades of gray: Interpretable and bias-aware reward modeling for human preferences
Simona-Vasilica Oprea, Adela Bâra · Apr 1, 2026 · Citations: 0
Pairwise Preference Automatic Metrics
Using the Anthropic HHRLHF dataset, we evaluate ten diverse large language models LLMs under a standard pairwise preference setting, where baseline performance remains below 0.74 ROC AUC, highlighting the difficulty of the task.
- Learning Diagnostic Reasoning for Decision Support in Toxicology
Nico Oberländer, David Bani-Harouni, Tobias Zellner, Nassir Navab, Florian Eyer · Mar 31, 2026 · Citations: 0
Expert Verification Automatic Metrics
To address this, we present DeToxR (Decision-support for Toxicology with Reasoning), the first adaptation of Reinforcement Learning (RL) to emergency toxicology.
- MemRerank: Preference Memory for Personalized Product Reranking
Zhiyuan Peng, Xuyang Wu, Huaixiao Tou, Yi Fang, Yu Gong · Mar 31, 2026 · Citations: 0
Pairwise Preference Automatic Metrics
LLM-based shopping agents increasingly rely on long purchase histories and multi-turn interactions for personalization, yet naively appending raw history to prompts is often ineffective due to noise, length, and relevance mismatch.
- Routing Sensitivity Without Controllability: A Diagnostic Study of Fairness in MoE Language Models
Junhyeok Lee, Kyu Sung Choi · Mar 28, 2026 · Citations: 0
Pairwise Preference Automatic Metrics
FARE reveals that routing-level preference shifts are either unachievable (Mixtral, Qwen1.5, Qwen3), statistically non-robust (DeepSeekMoE), or accompanied by substantial utility cost (OLMoE, -4.4%p CrowS-Pairs at -6.3%p TQA).
- Towards Reward Modeling for AI Tutors in Math Mistake Remediation
Kseniia Petukhova, Ekaterina Kochmar · Mar 25, 2026 · Citations: 0
Pairwise Preference Automatic Metrics
We develop and release Bradley-Terry preference models trained on weighted-sum rankings that we automatically create from MRBench, synthetic pairs, and data combinations.
- Semantic Alignment across Ancient Egyptian Language Stages via Normalization-Aware Multitask Learning
He Huang · Mar 25, 2026 · Citations: 0
Pairwise Preference Automatic Metrics
We evaluate alignment quality using pairwise metrics, specifically ROC-AUC and triplet accuracy, on curated Egyptian-English and intra-Egyptian cognate datasets.
- LLM-Powered Workflow Optimization for Multidisciplinary Software Development: An Automotive Industry Case Study
Shuai Wang, Yinan Yu, Earl Barr, Dhasarathy Parthasarathy · Mar 22, 2026 · Citations: 0
Expert Verification Automatic Metrics
We evaluate our approach on spapi, a production in-vehicle API system at Volvo Group involving 192 endpoints, 420 properties, and 776 CAN signals across six functional domains.
- A Comparative Empirical Study of Catastrophic Forgetting Mitigation in Sequential Task Adaptation for Continual Natural Language Processing Systems
Aram Abrahamyan, Sachin Kumar · Mar 19, 2026 · Citations: 0
Pairwise Preference Automatic Metrics
Performance is assessed with average accuracy, macro F1, and backward transfer, capturing the stability-plasticity trade-off across the task sequence.
- Decision-Level Ordinal Modeling for Multimodal Essay Scoring with Large Language Models
Han Zhang, Jiamin Su, Li liu · Mar 16, 2026 · Citations: 0
Rubric Rating Automatic Metrics
Experiments on the multimodal EssayJudge dataset show that DLOM improves over a generation-based SFT baseline across scoring traits, and DLOM-GF yields further gains when modality relevance is heterogeneous.
- An Industrial-Scale Insurance LLM Achieving Verifiable Domain Mastery and Hallucination Control without Competence Trade-offs
Qian Zhu, Xinnan Guo, Jingjing Huo, Jun Li, Pan Liu · Mar 15, 2026 · Citations: 0
Expert VerificationRlaif Or Synthetic Feedback Automatic Metrics
Additionally, we release INSEva, the most comprehensive insurance benchmark to date (39k+ samples).
- Mind the Shift: Decoding Monetary Policy Stance from FOMC Statements with Large Language Models
Yixuan Tang, Yi Yang · Mar 15, 2026 · Citations: 0
Llm As JudgeAutomatic Metrics Long Horizon
Across four LLM backbones, DCS consistently outperforms supervised probes and LLM-as-judge baselines, achieving up to 71.1% accuracy on sentence-level hawkish--dovish classification.