- AD-Bench: A Real-World, Trajectory-Aware Advertising Analytics Benchmark for LLM Agents
Lingxiang Hu, Yiding Sun, Tianle Xia, Wenwei Li, Ming Xu · Feb 15, 2026 · Citations: 0
Expert Verification Simulation Env Long Horizon
While Large Language Model (LLM) agents have achieved remarkable progress in complex reasoning tasks, evaluating their performance in real-world environments has become a critical problem.
- Let's Think in Two Steps: Mitigating Agreement Bias in MLLMs with Self-Grounded Verification
Moises Andrade, Joonhyuk Cha, Brandon Ho, Vriksha Srihari, Karmesh Yadav · Jul 15, 2025 · Citations: 0
Pairwise Preference Automatic MetricsSimulation Env Long Horizon
We evaluate MLLM verifiers across web navigation, computer use, and robotics, spanning 13+ models, 28+ designs, and thousands of trajectories from diverse agents.
- CounselReflect: A Toolkit for Auditing Mental-Health Dialogues
Yahan Li, Chaohao Du, Zeyang Li, Christopher Chun Kuizon, Shupeng Cheng · Mar 31, 2026 · Citations: 0
Rubric RatingExpert Verification Human Eval Web Browsing
The system integrates two families of evaluation signals: (i) 12 model-based metrics produced by task-specific predictors, and (ii) rubric-based metrics that extend coverage via a literature-derived library (69 metrics) and user-defined…
- Is this Idea Novel? An Automated Benchmark for Judgment of Research Ideas
Tim Schopf, Michael Färber · Mar 11, 2026 · Citations: 0
Rubric Rating Human Eval
To address this, we introduce RINoBench, the first comprehensive benchmark for large-scale evaluation of research idea novelty judgments.
- Jailbreak Foundry: From Papers to Runnable Attacks for Reproducible Benchmarking
Zhicheng Fang, Jingjie Zheng, Chenxu Fu, Wei Xu · Feb 27, 2026 · Citations: 0
Red Team Llm As Judge Multi Agent
Jailbreak techniques for large language models (LLMs) evolve faster than benchmarks, making robustness estimates stale and difficult to compare across papers due to drift in datasets, harnesses, and judging protocols.
- Vision-DeepResearch Benchmark: Rethinking Visual and Textual Search for Multimodal Large Language Models
Yu Zeng, Wenxuan Huang, Zhen Fang, Shuang Chen, Yufan Shen · Feb 2, 2026 · Citations: 0
Expert Verification Automatic Metrics Web Browsing
However, evaluating these visual and textual search abilities is still difficult, and existing benchmarks have two major limitations.
- CricBench: A Multilingual Benchmark for Evaluating LLMs in Cricket Analytics
Vaibhav Devraj, Dhruv Kumar, Jagat Sesh Challa, Parth Agarwal, Navya Kommuri · Dec 26, 2025 · Citations: 0
Expert Verification Automatic Metrics
To investigate this potential capability gap, we present CricBench, a comprehensive benchmark suite for evaluating LLMs on specialized cricket data.
- Don't Pass@k: A Bayesian Framework for Large Language Model Evaluation
Mohsen Hariri, Amirhossein Samandar, Michael Hinczewski, Vipin Chaudhary · Oct 5, 2025 · Citations: 0
Rubric Rating Automatic MetricsSimulation Env
We present a principled Bayesian evaluation framework that replaces Pass@k and average accuracy over N trials (avg@N) with posterior estimates of a model's underlying success probability and credible intervals, yielding stable rankings and…
- StitchCUDA: An Automated Multi-Agents End-to-End GPU Programing Framework with Rubric-based Agentic Reinforcement Learning
Shiyang Li, Zijian Zhang, Winson Chen, Yuebo Luo, Mingyi Hong · Mar 3, 2026 · Citations: 0
Rubric Rating Automatic Metrics Multi Agent
To address the challenge, in this work, we propose StitchCUDA, a multi-agent framework for end-to-end GPU program generation, with three specialized agents: a Planner to orchestrate whole system design, a Coder dedicated to implementing it…
- Beyond the Resumé: A Rubric-Aware Automatic Interview System for Information Elicitation
Harry Stuart, Masahiro Kaneko, Timothy Baldwin · Mar 2, 2026 · Citations: 0
Rubric Rating Automatic Metrics
Effective hiring is integral to the success of an organisation, but it is very challenging to find the most suitable candidates because expert evaluation (e.g.\ interviews conducted by a technical manager) are expensive to deploy at scale.
- 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.
- When Users Change Their Mind: Evaluating Interruptible Agents in Long-Horizon Web Navigation
Henry Peng Zou, Chunyu Miao, Wei-Chieh Huang, Yankai Chen, Yue Zhou · Apr 1, 2026 · Citations: 0
Critique Edit Simulation Env Long Horizon
As LLM agents transition from short, static problem solving to executing complex, long-horizon tasks in dynamic environments, the ability to handle user interruptions, such as adding requirement or revising goals, during mid-task execution…
- VehicleMemBench: An Executable Benchmark for Multi-User Long-Term Memory in In-Vehicle Agents
Yuhao Chen, Yi Xu, Xinyun Ding, Xiang Fang, Shuochen Liu · Mar 25, 2026 · Citations: 0
Pairwise Preference Simulation Env Tool Use
With the growing demand for intelligent in-vehicle experiences, vehicle-based agents are evolving from simple assistants to long-term companions.
- Step 3.5 Flash: Open Frontier-Level Intelligence with 11B Active Parameters
Ailin Huang, Ang Li, Aobo Kong, Bin Wang, Binxing Jiao · Feb 11, 2026 · Citations: 0
Pairwise Preference Tool Use
We introduce Step 3.5 Flash, a sparse Mixture-of-Experts (MoE) model that bridges frontier-level agentic intelligence and computational efficiency.
- SparkMe: Adaptive Semi-Structured Interviewing for Qualitative Insight Discovery
David Anugraha, Vishakh Padmakumar, Diyi Yang · Feb 24, 2026 · Citations: 0
Expert Verification Automatic Metrics Multi Agent
Based on this formulation, we introduce SparkMe, a multi-agent LLM interviewer that performs deliberative planning via simulated conversation rollouts to select questions with high expected utility.
- Decoupling Strategy and Execution in Task-Focused Dialogue via Goal-Oriented Preference Optimization
Jingyi Xu, Xingyu Ren, Zhoupeng Shou, Yumeng Zhang, Zhiqiang You · Jan 24, 2026 · Citations: 0
Pairwise Preference Automatic Metrics Long Horizon
To address this, we propose Goal-Oriented Preference Optimization (GOPO), a hierarchical reinforcement learning framework that decouples strategy planning from response generation via an Expert Agent and a Customer Service Agent.
- Document Reconstruction Unlocks Scalable Long-Context RLVR
Yao Xiao, Lei Wang, Yue Deng, Guanzheng Chen, Ziqi Jin · Feb 9, 2026 · Citations: 0
Rubric Rating Automatic Metrics
However, it often relies on gold-standard answers or explicit evaluation rubrics provided by powerful teacher models or human experts, which are costly and time-consuming.
- AJAR: Adaptive Jailbreak Architecture for Red-teaming
Yipu Dou, Wang Yang · Jan 16, 2026 · Citations: 0
Red Team Simulation Env
Large language model (LLM) safety evaluation is moving from content moderation to action security as modern systems gain persistent state, tool access, and autonomous control loops.
- IntelliAsk: Learning to Ask High-Quality Research Questions via RLVR
Karun Sharma, Vidushee Vats, Shengzhi Li, Yuxiang Wang, Zhongtian Sun · Jan 23, 2026 · Citations: 0
Pairwise PreferenceExpert Verification Human Eval
Peer review relies on substantive, evidence-based questions, yet current LLMs generate surface-level queries that perform worse than human reviewer questions in expert evaluation.
- Automatically Benchmarking LLM Code Agents through Agent-Driven Annotation and Evaluation
Lingyue Fu, Bolun Zhang, Hao Guan, Yaoming Zhu, Lin Qiu · Oct 28, 2025 · Citations: 0
Expert Verification Llm As JudgeAutomatic Metrics
To address these challenges, we propose an agent-driven benchmark construction pipeline that leverages human supervision to efficiently generate diverse project-level tasks.
- 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.
- RewardUQ: A Unified Framework for Uncertainty-Aware Reward Models
Daniel Yang, Samuel Stante, Florian Redhardt, Lena Libon, Parnian Kassraie · Feb 27, 2026 · Citations: 0
Pairwise Preference Automatic Metrics
Reward models are central to aligning large language models (LLMs) with human preferences.
- MENLO: From Preferences to Proficiency -- Evaluating and Modeling Native-like Quality Across 47 Languages
Chenxi Whitehouse, Sebastian Ruder, Tony Lin, Oksana Kurylo, Haruka Takagi · Sep 30, 2025 · Citations: 0
Pairwise PreferenceRubric Rating Automatic Metrics
To address this, we introduce MENLO, a framework that operationalizes the evaluation of native-like response quality based on audience design-inspired mechanisms.
- Automated Coding of Communication Data Using ChatGPT: Consistency Across Subgroups
Jiangang Hao, Wenju Cui, Patrick Kyllonen, Emily Kerzabi · Oct 23, 2025 · Citations: 0
Rubric Rating Human EvalAutomatic Metrics
Prior research has established that ChatGPT can be directly instructed with coding rubrics to code the communication data and achieves accuracy comparable to human raters.
- Vibe Code Bench: Evaluating AI Models on End-to-End Web Application Development
Hung Tran, Langston Nashold, Rayan Krishnan, Antoine Bigeard, Alex Gu · Mar 4, 2026 · Citations: 0
Pairwise Preference Automatic Metrics Web Browsing
We introduce Vibe Code Bench, a benchmark of 100 web application specifications (50 public validation, 50 held-out test) with 964 browser-based workflows comprising 10,131 substeps, evaluated against deployed applications by an autonomous…
- 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…
- 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.
- Do Compact SSL Backbones Matter for Audio Deepfake Detection? A Controlled Study with RAPTOR
Ajinkya Kulkarni, Sandipana Dowerah, Atharva Kulkarni, Tanel Alumäe, Mathew Magimai Doss · Mar 6, 2026 · Citations: 0
Pairwise Preference Long Horizon
We present RAPTOR, Representation Aware Pairwise-gated Transformer for Out-of-domain Recognition a controlled study of compact SSL backbones from the HuBERT and WavLM within a unified pairwise-gated fusion detector, evaluated across 14…
- $V_1$: Unifying Generation and Self-Verification for Parallel Reasoners
Harman Singh, Xiuyu Li, Kusha Sareen, Monishwaran Maheswaran, Sijun Tan · Mar 4, 2026 · Citations: 0
Pairwise Preference Automatic Metrics
On code generation (LiveCodeBench, CodeContests, SWE-Bench) and math reasoning (AIME, HMMT) benchmarks, V_1-Infer improves Pass@1 by up to 10% over pointwise verification and outperforms recent test-time scaling methods while being…
- Symphonym: Universal Phonetic Embeddings for Cross-Script Name Matching
Stephen Gadd · Jan 11, 2026 · Citations: 0
Expert Verification Automatic Metrics
Trained on 32.7 million triplet samples drawn from 67 million toponyms spanning GeoNames, Wikidata, and the Getty Thesaurus of Geographic Names, the Student achieves the highest Recall@1 (85.2%) and Mean Reciprocal Rank (90.8%) on the…
- Team of Thoughts: Efficient Test-time Scaling of Agentic Systems through Orchestrated Tool Calling
Jeffrey T. H. Wong, Zixi Zhang, Junyi Liu, Yiren Zhao · Feb 18, 2026 · Citations: 0
Automatic Metrics Multi Agent
Existing Multi-Agent Systems (MAS) typically rely on homogeneous model configurations, failing to exploit the diverse expertise inherent in different post-trained architectures.
- KLong: Training LLM Agent for Extremely Long-horizon Tasks
Yue Liu, Yingwei Ma, Yibo Miao, Yanhao Li, Yuchong Xie · Feb 19, 2026 · Citations: 0
Rubric Rating Long Horizon
Then, we introduce Research-Factory, an automated pipeline that generates high-quality training data by collecting research papers and constructing evaluation rubrics.
- Efficient Agent Training for Computer Use
Yanheng He, Jiahe Jin, Pengfei Liu · May 20, 2025 · Citations: 0
Demonstrations Long Horizon
We introduce PC Agent-E, an efficient agent training framework that significantly reduces reliance on large-scale human demonstrations.
- WebCoderBench: Benchmarking Web Application Generation with Comprehensive and Interpretable Evaluation Metrics
Chenxu Liu, Yingjie Fu, Wei Yang, Ying Zhang, Tao Xie · Jan 5, 2026 · Citations: 0
Pairwise Preference Llm As Judge
However, building a benchmark for LLM-generated web apps remains challenging due to the need for real-world user requirements, generalizable evaluation metrics without relying on ground-truth implementations or test cases, and interpretable…
- EasyAnimate: High-Performance Video Generation Framework with Hybrid Windows Attention and Reward Backpropagation
Jiaqi Xu, Kunzhe Huang, Xinyi Zou, Yunkuo Chen, Bo Liu · May 29, 2024 · Citations: 0
Pairwise Preference Human Eval
To enhance video generation quality, we optimize EasyAnimate using reward backpropagation to better align with human preferences.
- Tutoring Large Language Models to be Domain-adaptive, Precise, and Safe
Somnath Banerjee · Feb 14, 2026 · Citations: 0
Pairwise Preference Long Horizon
The methodological trajectory moves from classical supervised adaptation for task-specific demands to decoding-time alignment for safety, finally leveraging human feedback and preference modeling to achieve sociolinguistic acuity.
- From Pixels to Policies: Reinforcing Spatial Reasoning in Language Models for Content-Aware Layout Design
Sha Li, Stefano Petrangeli, Yu Shen, Xiang Chen · Feb 14, 2026 · Citations: 0
Critique Edit Simulation Env
We introduce LaySPA, a reinforcement learning framework that equips large language models (LLMs) with explicit and interpretable spatial reasoning for content-aware graphic layout design.
- Cross-Cultural Expert-Level Art Critique Evaluation with Vision-Language Models
Haorui Yu, Xuehang Wen, Fengrui Zhang, Qiufeng Yi · Jan 12, 2026 · Citations: 0
Rubric RatingCritique Edit
Existing benchmarks assess perception without interpretation, and common evaluation proxies, such as automated metrics and LLM-judge averaging, are unreliable for culturally sensitive generative tasks.
- 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.
- 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…
- Sabiá-4 Technical Report
Thiago Laitz, Thales Sales Almeida, Hugo Abonizio, Roseval Malaquias Junior, Giovana Kerche Bonás · Mar 10, 2026 · Citations: 0
Pairwise Preference Automatic Metrics Tool Use
The models were developed through a four-stage training pipeline: continued pre-training on Portuguese and Brazilian legal corpora, long-context extension to 128K tokens, supervised fine-tuning on instruction data spanning chat, code, legal…
- LIT-RAGBench: Benchmarking Generator Capabilities of Large Language Models in Retrieval-Augmented Generation
Koki Itai, Shunichi Hasegawa, Yuta Yamamoto, Gouki Minegishi, Masaki Otsuki · Mar 6, 2026 · Citations: 0
Llm As JudgeAutomatic Metrics Long Horizon
To bridge the gap between existing evaluations and practical use, we introduce LIT-RAGBench (the Logic, Integration, Table, Reasoning, and Abstention RAG Generator Benchmark), which defines five categories: Integration, Reasoning, Logic,…
- Can Large Language Models Replace Human Coders? Introducing ContentBench
Michael Haman · Feb 23, 2026 · Citations: 0
Critique Edit Automatic Metrics
This paper introduces ContentBench, a public benchmark suite that helps answer this replacement question by tracking how much agreement low-cost LLMs achieve and what they cost on the same interpretive coding tasks.
- PrivAct: Internalizing Contextual Privacy Preservation via Multi-Agent Preference Training
Yuhan Cheng, Hancheng Ye, Hai Helen Li, Jingwei Sun, Yiran Chen · Feb 14, 2026 · Citations: 0
Pairwise Preference Automatic Metrics Multi Agent
We propose PrivAct, a contextual privacy-aware multi-agent learning framework that internalizes contextual privacy preservation directly into models' generation behavior for privacy-compliant agentic actions.
- MARS: toward more efficient multi-agent collaboration for LLM reasoning
Xiao Wang, Jia Wang, Yijie Wang, Pengtao Dang, Sha Cao · Sep 24, 2025 · Citations: 0
Critique Edit Automatic Metrics Multi Agent
Large language models (LLMs) have achieved impressive results in natural language understanding, yet their reasoning capabilities remain limited when operating as single agents.
- Dyslexify: A Mechanistic Defense Against Typographic Attacks in CLIP
Lorenz Hufe, Constantin Venhoff, Erblina Purelku, Maximilian Dreyer, Sebastian Lapuschkin · Aug 28, 2025 · Citations: 0
Red Team Automatic Metrics
These models serve as suitable drop-in replacements for a broad range of safety-critical applications, where the risks of text-based manipulation outweigh the utility of text recognition.
- LaTeXTrans: Structured LaTeX Translation with Multi-Agent Coordination
Ziming Zhu, Chenglong Wang, Haosong Xv, Shunjie Xing, Yifu Huo · Aug 26, 2025 · Citations: 0
Demonstrations Automatic Metrics Multi Agent
In this paper, we introduce LaTeXTrans, a collaborative multi-agent system designed to address this challenge.
- MAS-ZERO: Designing Multi-Agent Systems with Zero Supervision
Zixuan Ke, Austin Xu, Yifei Ming, Xuan-Phi Nguyen, Ryan Chin · May 21, 2025 · Citations: 0
Critique Edit Automatic Metrics Multi Agent
Multi-agent systems (MAS) leveraging the impressive capabilities of Large Language Models (LLMs) hold significant potential for tackling complex tasks.
- FrameRef: A Framing Dataset and Simulation Testbed for Modeling Bounded Rational Information Health
Victor De Lima, Jiqun Liu, Grace Hui Yang · Feb 17, 2026 · Citations: 0
Human EvalSimulation Env Long Horizon
Within this framework, we construct framing-sensitive agent personas by fine-tuning language models with framing-conditioned loss attenuation, inducing targeted biases while preserving overall task competence.
- Supervised Reinforcement Learning: From Expert Trajectories to Step-wise Reasoning
Yihe Deng, I-Hung Hsu, Jun Yan, Zifeng Wang, Rujun Han · Oct 29, 2025 · Citations: 0
Demonstrations Long Horizon
Beyond reasoning benchmarks, SRL generalizes effectively to agentic software engineering tasks, establishing it as a robust and versatile training framework for reasoning-oriented LLMs.
- LUDOBENCH: Evaluating LLM Behavioural Decision-Making Through Spot-Based Board Game Scenarios in Ludo
Ojas Jain, Dhruv Kumar · Apr 7, 2026 · Citations: 0
Simulation Env Multi Agent
We introduce LudoBench, a benchmark for evaluating LLM strategic reasoning in Ludo, a stochastic multi-agent board game whose dice mechanics, piece capture, safe-square navigation, and home-path progression introduce meaningful planning…
- Small Reward Models via Backward Inference
Yike Wang, Faeze Brahman, Shangbin Feng, Teng Xiao, Hannaneh Hajishirzi · Feb 14, 2026 · Citations: 0
Rubric Rating Llm As Judge
However, the dominant LLM-as-a-Judge paradigm relies on the strong reasoning capabilities of large models, while alternative approaches require reference responses or explicit rubrics, limiting flexibility and broader accessibility.
- Incentivizing Agentic Reasoning in LLM Judges via Tool-Integrated Reinforcement Learning
Ran Xu, Jingjing Chen, Jiayu Ye, Yu Wu, Jun Yan · Oct 27, 2025 · Citations: 0
Pairwise Preference Human Eval
Motivated by the success of tool-integrated reasoning (TIR) in numerous tasks, we propose TIR-Judge, an end-to-end RL framework for training LLM judges that integrates a code executor for precise evaluation.
- Penalizing Length: Uncovering Systematic Bias in Quality Estimation Metrics
Yilin Zhang, Wenda Xu, Zhongtao Liu, Tetsuji Nakagawa, Markus Freitag · Oct 24, 2025 · Citations: 0
Pairwise Preference Llm As Judge
Quality Estimation (QE) metrics are vital in machine translation for reference-free evaluation and increasingly serve as selection criteria in data filtering and candidate reranking.
- On Discovering Algorithms for Adversarial Imitation Learning
Shashank Reddy Chirra, Jayden Teoh, Praveen Paruchuri, Pradeep Varakantham · Oct 1, 2025 · Citations: 0
Demonstrations Simulation Env
RA functions in AIL are typically derived from divergence minimization objectives, relying heavily on human design and ingenuity.
- LiveMCPBench: Can Agents Navigate an Ocean of MCP Tools?
Guozhao Mo, Wenliang Zhong, Jiawei Chen, Qianhao Yuan, Xuanang Chen · Aug 3, 2025 · Citations: 0
Llm As Judge 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…
- ScholarEval: Research Idea Evaluation Grounded in Literature
Hanane Nour Moussa, Patrick Queiroz Da Silva, Daniel Adu-Ampratwum, Alyson East, Zitong Lu · Oct 17, 2025 · Citations: 0
Rubric Rating
As AI tools become increasingly common for research ideation, robust evaluation is critical to ensure the validity and usefulness of generated ideas.
- 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.
- 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.