7 papers · 1 filter
OPERA: Aligning Open-Ended Reasoning via Objective Perplexity-based Reinforcement Learning
Wenxuan Jiang, Zining Fan, Zijian Zhang +6
Reinforcement Learning (RL) has enabled LLMs to excel in objective reasoning tasks such as mathematics and code generation. However, applying RL to open-ended tasks, such as creati…
General365: Benchmarking General Reasoning in Large Language Models Across Diverse and Challenging Tasks
Junlin Liu, Shengnan An, Shuang Zhou +10
Contemporary large language models (LLMs) have demonstrated remarkable reasoning capabilities, particularly in specialized domains like mathematics and physics. However, their abil…
TR-ICRL: Test-Time Rethinking for In-Context Reinforcement Learning
Wenxuan Jiang, Yuxin Zuo, Zijian Zhang +8
In-Context Reinforcement Learning (ICRL) enables Large Language Models (LLMs) to learn online from external rewards directly within the context window. However, a central challenge…
UniHetero: Could Generation Enhance Understanding for Vision-Language-Model at Large Data Scale?
Fengjiao Chen, Minhao Jing, Weitao Lu +3
Vision-language large models are moving toward the unification of visual understanding and visual generation tasks. However, whether generation can enhance understanding is still u…
AMO-Bench: Large Language Models Still Struggle in High School Math Competitions
Shengnan An, Xunliang Cai, Xuezhi Cao +8
We present AMO-Bench, an Advanced Mathematical reasoning benchmark with Olympiad level or even higher difficulty, comprising 50 human-crafted problems. Existing benchmarks have wid…
UNO-Bench: A Unified Benchmark for Exploring the Compositional Law Between Uni-modal and Omni-modal in Omni Models
Chen Chen, ZeYang Hu, Fengjiao Chen +6
Multimodal Large Languages models have been progressing from uni-modal understanding toward unifying visual, audio and language modalities, collectively termed omni models. However…