7 papers · 1 filter
LP-SFT: Local-Preserving Supervised Fine-Tuning via Multimodal Entropy Structure
Yueyang Wang, Baolong Bi, Shuo Lu +2
Supervised fine-tuning (SFT) is the standard approach for adapting pretrained language models to downstream domains, yet it often improves target-domain behavior at the cost of deg…
Scaling Latent Reasoning via Looped Language Models
Rui-Jie Zhu, Zixuan Wang, Kai Hua +30
Modern LLMs are trained to "think" primarily via explicit text generation, such as chain-of-thought (CoT), which defers reasoning to post-training and under-leverages pre-training…
OProver: A Unified Framework for Agentic Formal Theorem Proving
David Ma, Kaijing Ma, Shawn Guo +7
Recent progress in formal theorem proving has benefited from large-scale proof generation and verifier-aware training, but agentic proving is rarely integrated into prover training…
COIG-Writer: A High-Quality Dataset for Chinese Creative Writing with Thought Processes
Yunwen Li, Shuangshuang Ying, Xingwei Qu +16
Large language models exhibit systematic deficiencies in creative writing, particularly in non-English contexts where training data is scarce and lacks process-level supervision. W…
P2P: Automated Paper-to-Poster Generation and Fine-Grained Benchmark
Tao Sun, Enhao Pan, Zhengkai Yang +8
Academic posters are vital for scholarly communication, yet their manual creation is time-consuming. However, automated academic poster generation faces significant challenges in p…
KORGym: A Dynamic Game Platform for LLM Reasoning Evaluation
Jiajun Shi, Jian Yang, Jiaheng Liu +26
Recent advancements in large language models (LLMs) underscore the need for more comprehensive evaluation methods to accurately assess their reasoning capabilities. Existing benchm…