7 papers
Making Image Editing Easier via Adaptive Task Reformulation with Agentic Executions
Bo Zhao, Kairui Guo, Runnan Du +6
Instruction guided image editing has advanced substantially with recent generative models, yet it still fails to produce reliable results across many seemingly simple cases. We obs…
XFinBench: Benchmarking LLMs in Complex Financial Problem Solving and Reasoning
Zhihan Zhang, Yixin Cao, Lizi Liao
Solving financial problems demands complex reasoning, multimodal data processing, and a broad technical understanding, presenting unique challenges for current large language model…
Boosting Chart-to-Code Generation in MLLM via Dual Preference-Guided Refinement
Zhihan Zhang, Yixin Cao, Lizi Liao
Translating chart images into executable plotting scripts-referred to as the chart-to-code generation task-requires Multimodal Large Language Models (MLLMs) to perform fine-grained…
Good Learners Think Their Thinking: Generative PRM Makes Large Reasoning Model More Efficient Math Learner
Tao He, Rongchuan Mu, Lizi Liao +3
Large reasoning models (LRMs) have recently shown promise in solving complex math problems when optimized with Reinforcement Learning (RL). But conventional approaches rely on outc…
Com: A Causal-Guided Benchmark for Exploring Complex Commonsense Reasoning in Large Language Models
Kai Xiong, Xiao Ding, Yixin Cao +7
Large language models (LLMs) have mastered abundant simple and explicit commonsense knowledge through pre-training, enabling them to achieve human-like performance in simple common…
Simulation-Free Hierarchical Latent Policy Planning for Proactive Dialogues
Tao He, Lizi Liao, Yixin Cao +5
Recent advancements in proactive dialogues have garnered significant attention, particularly for more complex objectives (e.g. emotion support and persuasion). Unlike traditional t…