This work introduces ChartAnno, a comprehensive benchmark for evaluating MLLMs on chart annotation generation, and develops a multidimensional evaluation framework combining rule-based and LLM-judged metrics to assess execution, structural compliance, semantic consistency, and design effectiveness.
Zhenghan Chen, Zekai Shao, Lidan Tan et al.· 0 citations
FACTOR is introduced, which uses checkpoint-calibrated TD residuals to assign per-action credits that telescope to the trajectory advantage, and feedback-conditioned teacher-student likelihood gaps to allocate each credit across the realized action tokens.
Li-Chao Ma, Yang Sun, Shuai Zhao et al.· 3 citations
It is shown that policy entropy bounds both the policy gradient and probability update norms; consequently, entropy collapse effectively stops reward signal backpropagation, preventing further policy learning regardless of data quality.
Cong Qin, Jiaye Lin, Xiaoliang Fu et al.· Proceedings of the 32nd ACM...· 0 citations
Multimodal large language models (MLLMs) have made significant progress in chart understanding, generation, and editing, but their ability to annotate existing charts remains underexplored. Annotating charts is a common yet challenging communicative task, requiring models to infer intended messages, interpret chart sem...
Zhenghan Chen, Zekai Shao, Lidan Tan et al.· 0 citations
Reinforcement Learning with Verifiable Rewards (RLVR) has become a standard approach for improving complex reasoning in Large Language Models (LLMs). However, entropy collapse remains a critical bottleneck, often leading to performance degradation. While typically attributed to reduced exploration, we identify a more s...
Cong Qin, Jiaye Lin, Xiaoliang Fu et al.· Proceedings of the 32nd ACM...· 0 citations
Group-Reflective Self-Distillation (GRSD), which derives capability-aligned and outcome-discriminative guidance from the policy's own verified rollouts, and refines turn-level credit assignment by modulating outcome-based advantages while preserving the verifier-determined learning direction.
