- 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)…
- 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
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.
- $V_1$: 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…
- 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.
- 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
Then, we introduce Research-Factory, an automated pipeline that generates high-quality training data by collecting research papers and constructing evaluation rubrics.
- 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.
- 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.
- Learning When to Sample: Confidence-Aware Self-Consistency for Efficient LLM Chain-of-Thought Reasoning
Juming Xiong, Kevin Guo, Congning Ni, Chao Yan, Katherine Brown · Mar 9, 2026 · Citations: 0
Automatic Metrics
Recent self-consistency-based approaches further improve accuracy but require sampling and aggregating multiple reasoning trajectories, leading to substantial additional computational overhead.
- SWE-Protégé: Learning to Selectively Collaborate With an Expert Unlocks Small Language Models as Software Engineering Agents
Patrick Tser Jern Kon, Archana Pradeep, Ang Chen, Alexander P. Ellis, Warren Hunt · Feb 25, 2026 · Citations: 0
Automatic Metrics
Our approach combines supervised fine-tuning on expert-augmented trajectories with agentic reinforcement learning that explicitly discourages degenerative looping and unproductive expert collaboration.
- 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 --…
- 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).
- Structurally Aligned Subtask-Level Memory for Software Engineering Agents
Kangning Shen, Jingyuan Zhang, Chenxi Sun, Wencong Zeng, Yang Yue · Feb 25, 2026 · Citations: 0
Automatic Metrics
Large Language Models (LLMs) have demonstrated significant potential as autonomous software engineering (SWE) agents.
- Cross-Context Verification: Hierarchical Detection of Benchmark Contamination through Session-Isolated Analysis
Tae-Eun Song · Mar 23, 2026 · Citations: 0
Automatic Metrics
LLM coding benchmarks face a credibility crisis: widespread solution leakage and test quality issues undermine SWE-bench Verified, while existing detection methods--paraphrase consistency, n-gram overlap, perplexity analysis--never directly…
- Confidence-Driven Multi-Scale Model Selection for Cost-Efficient Inference
Bo-Wei Chen, Chung-Chi Chen, An-Zi Yen · Feb 25, 2026 · Citations: 0
Automatic Metrics
Experiments on the Massive Multitask Language Understanding (MMLU) benchmark show that our approach achieves accuracy comparable to the largest model while reducing computational costs by 20\% to 40\%.
- TARo: Token-level Adaptive Routing for LLM Test-time Alignment
Arushi Rai, Qiang Zhang, Hanqing Zeng, Yunkai Zhang, Dipesh Tamboli · Mar 19, 2026 · Citations: 0
Pairwise Preference
Recent test-time alignment methods offer a lightweight alternative, but have been explored mainly for preference alignment rather than reasoning.
- Inducing Epistemological Humility in Large Language Models: A Targeted SFT Approach to Reducing Hallucination
Cem Uluoglakci, Tugba Taskaya Temizel · Mar 18, 2026 · Citations: 0
Pairwise Preference
We also release HypoTermQA-Enhanced, a benchmark for hallucination tendency strengthened through multiple validations.
- Long Grounded Thoughts: Synthesizing Visual Problems and Reasoning Chains at Scale
David Acuna, Chao-Han Huck Yang, Yuntian Deng, Jaehun Jung, Ximing Lu · Nov 7, 2025 · Citations: 0
Pairwise Preference
We introduce a framework able to synthesize vision-centric problems spanning diverse levels of complexity, and the resulting dataset with over 1M high-quality problems including: reasoning traces, preference data, and instruction prompts…
- 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.
- Towards Bridging the Reward-Generation Gap in Direct Alignment Algorithms
Zeguan Xiao, Yun Chen, Guanhua Chen, Ke Tang · Jun 11, 2025 · Citations: 0
Pairwise Preference
Direct Alignment Algorithms (DAAs), such as Direct Preference Optimization (DPO) and Simple Preference Optimization (SimPO), have emerged as efficient alternatives to Reinforcement Learning from Human Feedback (RLHF) algorithms for aligning…
- Modeling LLM Unlearning as an Asymmetric Two-Task Learning Problem
Zeguan Xiao, Siqing Li, Yong Wang, Xuetao Wei, Jian Yang · Apr 16, 2026 · Citations: 0
- C2: Scalable Rubric-Augmented Reward Modeling from Binary Preferences
Akira Kawabata, Saku Sugawara · Apr 15, 2026 · Citations: 0
- Hidden Measurement Error in LLM Pipelines Distorts Annotation, Evaluation, and Benchmarking
Solomon Messing · Apr 13, 2026 · Citations: 0
- SUPERNOVA: Eliciting General Reasoning in LLMs with Reinforcement Learning on Natural Instructions
Ashima Suvarna, Kendrick Phan, Mehrab Beikzadeh, Hritik Bansal, Saadia Gabriel · Apr 9, 2026 · Citations: 0
- Dead Weights, Live Signals: Feedforward Graphs of Frozen Language Models
Marcus Armstrong, Navid Ayoobi, Arjun Mukherjee · Apr 9, 2026 · Citations: 0
- Activation Steering for Aligned Open-ended Generation without Sacrificing Coherence
Niklas Herbster, Martin Zborowski, Alberto Tosato, Gauthier Gidel, Tommaso Tosato · Apr 9, 2026 · Citations: 0
- Sensitivity-Positional Co-Localization in GQA Transformers
Manoj Chandrashekar Rao · Apr 9, 2026 · Citations: 0
- Symbiotic-MoE: Unlocking the Synergy between Generation and Understanding
Xiangyue Liu, Zijian Zhang, Miles Yang, Zhao Zhong, Liefeng Bo · Apr 9, 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
- Lie to Me: How Faithful Is Chain-of-Thought Reasoning in Reasoning Models?
Richard J. Young · Mar 23, 2026 · Citations: 0
- AdaRubric: Task-Adaptive Rubrics for LLM Agent Evaluation
Liang Ding · Mar 22, 2026 · Citations: 0
- FailureMem: A Failure-Aware Multimodal Framework for Autonomous Software Repair
Ruize Ma, Yilei Jiang, Shilin Zhang, Zheng Ma, Yi Feng · Mar 18, 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
- Are Large Language Models Truly Smarter Than Humans?
Eshwar Reddy M, Sourav Karmakar · Mar 17, 2026 · Citations: 0
- daVinci-Env: Open SWE Environment Synthesis at Scale
Dayuan Fu, Shenyu Wu, Yunze Wu, Zerui Peng, Yaxing Huang · Mar 13, 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
- Qwen3-Coder-Next Technical Report
Ruisheng Cao, Mouxiang Chen, Jiawei Chen, Zeyu Cui, Yunlong Feng · Feb 28, 2026 · Citations: 0
- SWE-rebench V2: Language-Agnostic SWE Task Collection at Scale
Ibragim Badertdinov, Maksim Nekrashevich, Anton Shevtsov, Alexander Golubev · Feb 27, 2026 · Citations: 0
- Rethinking the Value of Agent-Generated Tests for LLM-Based Software Engineering Agents
Zhi Chen, Zhensu Sun, Yuling Shi, Chao Peng, Xiaodong Gu · Feb 8, 2026 · Citations: 0
- LLMOrbit: A Circular Taxonomy of Large Language Models -From Scaling Walls to Agentic AI Systems
Badri N. Patro, Vijay S. Agneeswaran · Jan 20, 2026 · Citations: 0
- Latent Self-Consistency for Reliable Majority-Set Selection in Short- and Long-Answer Reasoning
Jungsuk Oh, Jay-Yoon Lee · Aug 25, 2025 · Citations: 0
- Darwin Godel Machine: Open-Ended Evolution of Self-Improving Agents
Jenny Zhang, Shengran Hu, Cong Lu, Robert Lange, Jeff Clune · May 29, 2025 · Citations: 0
- Beyond Final Code: A Process-Oriented Error Analysis of Software Development Agents in Real-World GitHub Scenarios
Zhi Chen, Wei Ma, Lingxiao Jiang · Mar 16, 2025 · Citations: 0