2 citations · 2 across the 9 of their papers we have counts for
7 papers · 1 filter
Elo-Evolve: A Co-evolutionary Framework for Language Model Alignment
Jing Zhao, Ting Zhen, Junwei Bao +2
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 scarcit…
Quality-constrained Entropy Maximization Policy Optimization for LLM Diversity
Haihui Pan, Yuzhong Hong, Kaichen Zhang +4
In many large language model (LLM) alignment applications, users expect not only high-quality outputs but also substantial diversity. However, existing methods often face a fundame…
Measuring and Mitigating Post-hoc Rationalization in Reverse Chain-of-Thought Generation
Guangyue Peng, Zongchao Chen, Wen Luo +9
Reverse Chain-of-Thought Generation (RCG) synthesizes reasoning traces from query-answer pairs, but answer-visible generation can justify a pre-committed answer rather than derive…
Reasoning's Razor: Reasoning Improves Accuracy but Can Hurt Recall at Critical Operating Points in Safety and Hallucination Detection
Atoosa Chegini, Hamid Kazemi, Garrett Souza +5
Reasoning has become a central paradigm for large language models (LLMs), consistently boosting accuracy across diverse benchmarks. Yet its suitability for precision-sensitive task…
gpt-oss-120b & gpt-oss-20b Model Card
OpenAI, :, Sandhini Agarwal +124
We present gpt-oss-120b and gpt-oss-20b, two open-weight reasoning models that push the frontier of accuracy and inference cost. The models use an efficient mixture-of-expert trans…
Prompting is not Enough: Exploring Knowledge Integration and Controllable Generation
Tingjia Shen, Hao Wang, Chuan Qin +5
Open-domain question answering (OpenQA) represents a cornerstone in natural language processing (NLP), primarily focused on extracting answers from unstructured textual data. With…