Saved in:
| Main Authors: | Botta, Edoardo, Li, Yuchen, Mehta, Aashay, Ash, Jordan T., Zhang, Cyril, Risteski, Andrej |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2502.12123 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Promises and Pitfalls of Generative Masked Language Modeling: Theoretical Framework and Practical Guidelines
by: Li, Yuchen, et al.
Published: (2024)
by: Li, Yuchen, et al.
Published: (2024)
CodePDE: An Inference Framework for LLM-driven PDE Solver Generation
by: Li, Shanda, et al.
Published: (2025)
by: Li, Shanda, et al.
Published: (2025)
Self-Improvement in Language Models: The Sharpening Mechanism
by: Huang, Audrey, et al.
Published: (2024)
by: Huang, Audrey, et al.
Published: (2024)
Towards Active Synthetic Data Generation for Finetuning Language Models
by: Kessler, Samuel, et al.
Published: (2025)
by: Kessler, Samuel, et al.
Published: (2025)
Fit Like You Sample: Sample-Efficient Generalized Score Matching from Fast Mixing Diffusions
by: Qin, Yilong, et al.
Published: (2023)
by: Qin, Yilong, et al.
Published: (2023)
A computational phase transition for learning-to-sample from Ising models
by: Risteski, Andrej, et al.
Published: (2026)
by: Risteski, Andrej, et al.
Published: (2026)
SVIP: Towards Verifiable Inference of Open-source Large Language Models
by: Sun, Yifan, et al.
Published: (2024)
by: Sun, Yifan, et al.
Published: (2024)
Taming Imperfect Process Verifiers: A Sampling Perspective on Backtracking
by: Rohatgi, Dhruv, et al.
Published: (2025)
by: Rohatgi, Dhruv, et al.
Published: (2025)
Reinforcing General Reasoning without Verifiers
by: Zhou, Xiangxin, et al.
Published: (2025)
by: Zhou, Xiangxin, et al.
Published: (2025)
AutoPyVerifier: Learning Compact Executable Verifiers for Large Language Model Outputs
by: Pezeshkpour, Pouya, et al.
Published: (2026)
by: Pezeshkpour, Pouya, et al.
Published: (2026)
RL Tango: Reinforcing Generator and Verifier Together for Language Reasoning
by: Zha, Kaiwen, et al.
Published: (2025)
by: Zha, Kaiwen, et al.
Published: (2025)
Chart-RL: Generalized Chart Comprehension via Reinforcement Learning with Verifiable Rewards
by: Zhang, Xin, et al.
Published: (2026)
by: Zhang, Xin, et al.
Published: (2026)
CoVerRL: Breaking the Consensus Trap in Label-Free Reasoning via Generator-Verifier Co-Evolution
by: Pan, Teng, et al.
Published: (2026)
by: Pan, Teng, et al.
Published: (2026)
Annotation-Free Reinforcement Learning Query Rewriting via Verifiable Search Reward
by: Cha, Sungguk, et al.
Published: (2025)
by: Cha, Sungguk, et al.
Published: (2025)
Query Performance Explanation through Large Language Model for HTAP Systems
by: Xiu, Haibo, et al.
Published: (2024)
by: Xiu, Haibo, et al.
Published: (2024)
The tractability landscape of diffusion alignment: regularization, rewards, and computational primitives
by: Moitra, Ankur, et al.
Published: (2026)
by: Moitra, Ankur, et al.
Published: (2026)
Steering diffusion models with quadratic rewards: a fine-grained analysis
by: Moitra, Ankur, et al.
Published: (2026)
by: Moitra, Ankur, et al.
Published: (2026)
A Comprehensive Evaluation of Neural SPARQL Query Generation from Natural Language Questions
by: Diallo, Papa Abdou Karim Karou, et al.
Published: (2023)
by: Diallo, Papa Abdou Karim Karou, et al.
Published: (2023)
RLVE: Scaling Up Reinforcement Learning for Language Models with Adaptive Verifiable Environments
by: Zeng, Zhiyuan, et al.
Published: (2025)
by: Zeng, Zhiyuan, et al.
Published: (2025)
Empirical Analysis of Efficient Fine-Tuning Methods for Large Pre-Trained Language Models
by: Doering, Nigel, et al.
Published: (2024)
by: Doering, Nigel, et al.
Published: (2024)
CaLM: Contrasting Large and Small Language Models to Verify Grounded Generation
by: Hsu, I-Hung, et al.
Published: (2024)
by: Hsu, I-Hung, et al.
Published: (2024)
OptLLM: Optimal Assignment of Queries to Large Language Models
by: Liu, Yueyue, et al.
Published: (2024)
by: Liu, Yueyue, et al.
Published: (2024)
An Experimental Design Framework for Label-Efficient Supervised Finetuning of Large Language Models
by: Bhatt, Gantavya, et al.
Published: (2024)
by: Bhatt, Gantavya, et al.
Published: (2024)
Verifying the Verifiers: Unveiling Pitfalls and Potentials in Fact Verifiers
by: Seo, Wooseok, et al.
Published: (2025)
by: Seo, Wooseok, et al.
Published: (2025)
GenFighter: A Generative and Evolutive Textual Attack Removal
by: Islam, Md Athikul, et al.
Published: (2024)
by: Islam, Md Athikul, et al.
Published: (2024)
Towards Faithful and Robust LLM Specialists for Evidence-Based Question-Answering
by: Schimanski, Tobias, et al.
Published: (2024)
by: Schimanski, Tobias, et al.
Published: (2024)
VerifierQ: Enhancing LLM Test Time Compute with Q-Learning-based Verifiers
by: Qi, Jianing, et al.
Published: (2024)
by: Qi, Jianing, et al.
Published: (2024)
Towards Verifiable Text Generation with Symbolic References
by: Hennigen, Lucas Torroba, et al.
Published: (2023)
by: Hennigen, Lucas Torroba, et al.
Published: (2023)
SCI-Verifier: Scientific Verifier with Thinking
by: Zheng, Shenghe, et al.
Published: (2025)
by: Zheng, Shenghe, et al.
Published: (2025)
Large Language Models to Diffusion Finetuning
by: Cetin, Edoardo, et al.
Published: (2025)
by: Cetin, Edoardo, et al.
Published: (2025)
Resolving UnderEdit & OverEdit with Iterative & Neighbor-Assisted Model Editing
by: Baghel, Bhiman Kumar, et al.
Published: (2025)
by: Baghel, Bhiman Kumar, et al.
Published: (2025)
AMGPT: a Large Language Model for Contextual Querying in Additive Manufacturing
by: Chandrasekhar, Achuth, et al.
Published: (2024)
by: Chandrasekhar, Achuth, et al.
Published: (2024)
Towards High Data Efficiency in Reinforcement Learning with Verifiable Reward
by: Tang, Xinyu, et al.
Published: (2025)
by: Tang, Xinyu, et al.
Published: (2025)
Do You Know What You Are Talking About? Characterizing Query-Knowledge Relevance For Reliable Retrieval Augmented Generation
by: Li, Zhuohang, et al.
Published: (2024)
by: Li, Zhuohang, et al.
Published: (2024)
Search, Verify and Feedback: Towards Next Generation Post-training Paradigm of Foundation Models via Verifier Engineering
by: Guan, Xinyan, et al.
Published: (2024)
by: Guan, Xinyan, et al.
Published: (2024)
Self-Verified Distillation: Your Language Model Is Secretly Its Own Synthetic Data Pipeline
by: Lee, Tony, et al.
Published: (2026)
by: Lee, Tony, et al.
Published: (2026)
RLPR: Extrapolating RLVR to General Domains without Verifiers
by: Yu, Tianyu, et al.
Published: (2025)
by: Yu, Tianyu, et al.
Published: (2025)
Verifier-Backed Hard Problem Generation for Mathematical Reasoning
by: Lai, Yuhang, et al.
Published: (2026)
by: Lai, Yuhang, et al.
Published: (2026)
Complex Logical Instruction Generation
by: Zhang, Mian, et al.
Published: (2025)
by: Zhang, Mian, et al.
Published: (2025)
Was it Slander? Towards Exact Inversion of Generative Language Models
by: Skapars, Adrians, et al.
Published: (2024)
by: Skapars, Adrians, et al.
Published: (2024)
Similar Items
-
Promises and Pitfalls of Generative Masked Language Modeling: Theoretical Framework and Practical Guidelines
by: Li, Yuchen, et al.
Published: (2024) -
CodePDE: An Inference Framework for LLM-driven PDE Solver Generation
by: Li, Shanda, et al.
Published: (2025) -
Self-Improvement in Language Models: The Sharpening Mechanism
by: Huang, Audrey, et al.
Published: (2024) -
Towards Active Synthetic Data Generation for Finetuning Language Models
by: Kessler, Samuel, et al.
Published: (2025) -
Fit Like You Sample: Sample-Efficient Generalized Score Matching from Fast Mixing Diffusions
by: Qin, Yilong, et al.
Published: (2023)