- 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.
- 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
Chain-of-thought (CoT) reasoning improves LLM accuracy, yet detecting failures cheaply remains elusive.
- RASPRef: Retrieval-Augmented Self-Supervised Prompt Refinement for Large Reasoning Models
Rahul Soni · Mar 27, 2026 · Citations: 0
Critique Edit
Recent reasoning-focused language models such as DeepSeek R1 and OpenAI o1 have demonstrated strong performance on structured reasoning benchmarks including GSM8K, MATH, and multi-hop question answering tasks.
- Think$^{2}$: Grounded Metacognitive Reasoning in Large Language Models
Abraham Paul Elenjical, Vivek Hruday Kavuri, Vasudeva Varma · Feb 21, 2026 · Citations: 0
Pairwise Preference Human Eval
We introduce a psychologically grounded metacognitive framework that operationalizes Ann Brown's regulatory cycle (Planning, Monitoring, and Evaluation) as a structured prompting architecture, and study its integration within a lightweight…
- 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…
- 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%).
- GIFT: Group-Relative Implicit Fine-Tuning Integrates GRPO with DPO and UNA
Zhichao Wang · Oct 27, 2025 · Citations: 0
Pairwise Preference Automatic Metrics
This paper proposes Group-relative Implicit Fine-Tuning (GIFT), a reinforcement learning framework for aligning large language models (LLMs) that unifies on-policy optimization with implicit preference learning.
- FOR-Prompting: From Objection to Revision via an Asymmetric Prompting Protocol
He Zhang, Anzhou Zhang, Jian Dai · Oct 2, 2025 · Citations: 0
Pairwise PreferenceCritique Edit Automatic Metrics
Beyond structured math tasks, FOR-Prompting supports refinement in open-ended and multi-stage tasks: qualitative analysis shows improved exploration, coverage, and specificity, and a blind study of human preferences found that participants…
- 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
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.
- S0 Tuning: Zero-Overhead Adaptation of Hybrid Recurrent-Attention Models
Jack Young · Apr 1, 2026 · Citations: 0
Automatic Metrics
Using roughly 48 execution-verified HumanEval training solutions, tuning a single initial state matrix per recurrent layer, with zero inference overhead, outperforms LoRA by +10.8 pp (p < 0.001) on HumanEval.
- Top-b: Entropic Regulation of Relative Probability Bands in Autoregressive Language Processes
Deepon Halder, Raj Dabre · Mar 15, 2026 · Citations: 0
Automatic Metrics
Empirical validation on GPQA and GSM8K benchmarks indicates that Top-b significantly reduces generation entropy and inter-decoding variance while maintaining competitive reasoning accuracy, effectively approximating a self-regulating…
- D-COT: Disciplined Chain-of-Thought Learning for Efficient Reasoning in Small Language Models
Shunsuke Ubukata · Feb 25, 2026 · Citations: 0
Automatic Metrics
In this study, we propose Disciplined Chain-of-Thought (D-CoT), a novel framework that enforces a structured reasoning process using control tags -- such as <TEMP_LOW> for fact-checking and <TEMP_HIGH> for multi-perspective exploration --…
- The Flexibility Trap: Why Arbitrary Order Limits Reasoning Potential in Diffusion Language Models
Zanlin Ni, Shenzhi Wang, Yang Yue, Tianyu Yu, Weilin Zhao · Jan 21, 2026 · Citations: 0
Automatic Metrics
We demonstrate that effective reasoning can be better elicited by intentionally forgoing arbitrary order and applying standard Group Relative Policy Optimization (GRPO) instead.
- Cache What Lasts: Token Retention for Memory-Bounded KV Cache in LLMs
Ngoc Bui, Shubham Sharma, Simran Lamba, Saumitra Mishra, Rex Ying · Dec 3, 2025 · Citations: 0
Automatic Metrics
Across mathematical reasoning (GSM8K, MATH-500, AIME24), procedural generation (LongProc), conversational long-memory benchmarks (LongMemEval), and long-context understanding (LongBenchV2 and SCBench), TRIM-KV consistently outperforms…
- SPARE: Single-Pass Annotation with Reference-Guided Evaluation for Automatic Process Supervision and Reward Modelling
Md Imbesat Hassan Rizvi, Xiaodan Zhu, Iryna Gurevych · Jun 18, 2025 · Citations: 0
Automatic Metrics
To address this, we introduce Single-Pass Annotation with Reference-Guided Evaluation (SPARE), a novel structured framework that enables efficient per-step annotation by jointly aligning solution steps to reference solutions and determine…
- PIKA: Expert-Level Synthetic Datasets for Post-Training Alignment from Scratch
Shangjian Yin, Shining Liang, Wenbiao Ding, Yuli Qian, Zhouxing Shi · Oct 8, 2025 · Citations: 0
Pairwise Preference
Despite its small size, fine-tuning Llama-3-8B-Base on PiKa-SFT even outperforms the official Llama-3-8B-Instruct model trained on over 10M proprietary examples on widely used benchmarks such as AlpacaEval 2.0 and Arena-Hard.
- Revisiting Self-Play Preference Optimization: On the Role of Prompt Difficulty
Yao Xiao, Jung-jae Kim, Roy Ka-wei Lee, Lidong Bing · Oct 7, 2025 · Citations: 0
Pairwise Preference
Self-play preference optimization has emerged as a prominent paradigm for aligning large language models (LLMs).
- Evaluation of Large Language Models via Coupled Token Generation
Nina Corvelo Benz, Stratis Tsirtsis, Eleni Straitouri, Ivi Chatzi, Ander Artola Velasco · Feb 3, 2025 · Citations: 0
Pairwise Preference
In this work, we argue that the evaluation and ranking of large language models should control for the randomization underpinning their functioning.
- DeepPrune: Parallel Scaling without Inter-trace Redundancy
Shangqing Tu, Yaxuan Li, Yushi Bai, Lei Hou, Juanzi Li · Oct 9, 2025 · Citations: 0
Llm As JudgeAutomatic Metrics
Our method features a specialized judge model trained with out-of-distribution data (AIME 2022, AIME 2023, and MATH 500) using oversampling techniques to accurately predict answer equivalence from partial reasoning traces, achieving 0.7072…
- Towards Hierarchical Multi-Step Reward Models for Enhanced Reasoning in Large Language Models
Teng Wang, Zhangyi Jiang, Zhenqi He, Shenyang Tong, Wenhan Yang · Mar 16, 2025 · Citations: 0
Automatic Metrics
Empirical results on the PRM800K dataset show that HRM, together with HNC, provides more stable and reliable evaluations than PRM.
- Examining Reasoning LLMs-as-Judges in Non-Verifiable LLM Post-Training
Yixin Liu, Yue Yu, DiJia Su, Sid Wang, Xuewei Wang · Mar 12, 2026 · Citations: 0
Pairwise Preference
Reasoning LLMs-as-Judges, which can benefit from inference-time scaling, provide a promising path for extending the success of reasoning models to non-verifiable domains where the output correctness/quality cannot be directly checked.
- Schema for In-Context Learning
Pan Chen, Shaohong Chen, Mark Wang, Shi Xuan Leong, Priscilla Fung · Oct 14, 2025 · Citations: 0
Demonstrations
Inspired by cognitive science, specifically schema theory, which holds that humans interpret new information by activating pre-existing mental frameworks (schemas) to structure understanding, we introduce Schema-Activated In-Context…
- Alignment through Meta-Weighted Online Sampling: Bridging the Gap between Data Generation and Preference Optimization
Junming Yang, Ning Xu, Biao Liu, Shiqi Qiao, Xin Geng · Sep 27, 2025 · Citations: 0
Pairwise Preference
To bridge this gap, we propose Meta-Weighted Adaptive Preference Optimization (MetaAPO), a novel framework that dynamically couples data generation with model training.
- A Third Paradigm for LLM Evaluation: Dialogue Game-Based Evaluation using clembench
David Schlangen, Sherzod Hakimov, Chalamalasetti Kranti, Jonathan Jordan, Philipp Sadler · Jul 11, 2025 · Citations: 0
Pairwise Preference
There are currently two main paradigms for evaluating large language models (LLMs), reference-based evaluation and preference-based evaluation.
- Search Arena: Analyzing Search-Augmented LLMs
Mihran Miroyan, Tsung-Han Wu, Logan King, Tianle Li, Jiayi Pan · Jun 5, 2025 · Citations: 0
Pairwise Preference
In this work, we introduce Search Arena, a crowd-sourced, large-scale, human-preference dataset of over 24,000 paired multi-turn user interactions with search-augmented LLMs.
- Think in Sentences: Explicit Sentence Boundaries Enhance Language Model's Capabilities
Zhichen Liu, Yongyuan Li, Yang Xu · Apr 11, 2026 · Citations: 0
- DMax: Aggressive Parallel Decoding for dLLMs
Zigeng Chen, Gongfan Fang, Xinyin Ma, Ruonan Yu, Xinchao Wang · Apr 9, 2026 · Citations: 0
- TEMPER: Testing Emotional Perturbation in Quantitative Reasoning
Atahan Dokme, Benjamin Reichman, Larry Heck · Apr 9, 2026 · Citations: 0
- Sensitivity-Positional Co-Localization in GQA Transformers
Manoj Chandrashekar Rao · Apr 9, 2026 · Citations: 0
- Squeeze Evolve: Unified Multi-Model Orchestration for Verifier-Free Evolution
Monishwaran Maheswaran, Leon Lakhani, Zhongzhu Zhou, Shijia Yang, Junxiong Wang · Apr 9, 2026 · Citations: 0
- Beyond the Assistant Turn: User Turn Generation as a Probe of Interaction Awareness in Language Models
Sarath Shekkizhar, Romain Cosentino, Adam Earle · Apr 2, 2026 · Citations: 0
- Is Mathematical Problem-Solving Expertise in Large Language Models Associated with Assessment Performance?
Liang Zhang, Yu Fu, Xinyi Jin · Mar 26, 2026 · Citations: 0
- Cross-Model Disagreement as a Label-Free Correctness Signal
Matt Gorbett, Suman Jana · Mar 26, 2026 · Citations: 0
- Efficient Detection of Bad Benchmark Items with Novel Scalability Coefficients
Michael Hardy, Joshua Gilbert, Benjamin Domingue · Mar 26, 2026 · Citations: 0
- Off-Policy Value-Based Reinforcement Learning for Large Language Models
Peng-Yuan Wang, Ziniu Li, Tian Xu, Bohan Yang, Tian-Shuo Liu · Mar 24, 2026 · Citations: 0
- Lie to Me: How Faithful Is Chain-of-Thought Reasoning in Reasoning Models?
Richard J. Young · Mar 23, 2026 · Citations: 0
- Mediocrity is the key for LLM as a Judge Anchor Selection
Shachar Don-Yehiya, Asaf Yehudai, Leshem Choshen, Omri Abend · Mar 17, 2026 · Citations: 0
- TERMINATOR: Learning Optimal Exit Points for Early Stopping in Chain-of-Thought Reasoning
Alliot Nagle, Jakhongir Saydaliev, Dhia Garbaya, Michael Gastpar, Ashok Vardhan Makkuva · Mar 13, 2026 · Citations: 0
- When LLM Judge Scores Look Good but Best-of-N Decisions Fail
Eddie Landesberg · Mar 12, 2026 · Citations: 0
- NeuroLoRA: Context-Aware Neuromodulation for Parameter-Efficient Multi-Task Adaptation
Yuxin Yang, Haoran Zhang, Mingxuan Li, Jiachen Xu, Ruoxi Shen · Mar 12, 2026 · Citations: 0
- In-Context Environments Induce Evaluation-Awareness in Language Models
Maheep Chaudhary · Mar 4, 2026 · Citations: 0
- CHIMERA: Compact Synthetic Data for Generalizable LLM Reasoning
Xinyu Zhu, Yihao Feng, Yanchao Sun, Xianzhi Du, Pingzhi Li · Mar 1, 2026 · Citations: 0
- SC-Arena: A Natural Language Benchmark for Single-Cell Reasoning with Knowledge-Augmented Evaluation
Jiahao Zhao, Feng Jiang, Shaowei Qin, Zhonghui Zhang, Junhao Liu · Feb 26, 2026 · Citations: 0
- SPG: Sandwiched Policy Gradient for Masked Diffusion Language Models
Chenyu Wang, Paria Rashidinejad, DiJia Su, Song Jiang, Sid Wang · Oct 10, 2025 · Citations: 0
- Bridging Draft Policy Misalignment: Group Tree Optimization for Speculative Decoding
Shijing Hu, Jingyang Li, Zhihui Lu, Pan Zhou · Sep 26, 2025 · Citations: 0
- An Automated Survey of Generative Artificial Intelligence: Large Language Models, Architectures, Protocols, and Applications
Eduardo C. Garrido-Merchán, Álvaro López López · Jun 5, 2023 · Citations: 0