Conversational agents have traditionally been developed for either task-oriented dialogue (TOD) or open-ended chitchat, with limited progress in unifying the two.Yet, real-world conversations naturally involve fluid transitions between these modes.To address this gap, we introduce TACT (TOD-And-Chitchat Transition), a dataset designed for transitionaware dialogue modeling that incorporates structurally diverse and integrated mode flows.TACT supports both user-and agent-driven mode switches, enabling robust modeling of complex conversational dynamics.To evaluate an agent's ability to initiate and recover from mode transitions, we propose two new metrics-Switch and Recovery.Models trained on TACT outperform baselines in both intent detection and mode transition handling.Moreover, applying Direct Preference Optimization (DPO) to TACT-trained models yields additional gains, achieving 75.74% joint mode-intent accuracy and a 70.1% win rate against GPT-4O in human evaluation.These results demonstrate that pairing structurally diverse data with DPO enhances response quality and transition control, paving the way for more proactive and transition-aware conversational agents.

To enhance the explainability of meeting summarization, we construct a new dataset called "ExplainMeetSum," an augmented version of QMSum, by newly annotating evidence sentences that faithfully "explain" a summary.Using ExplainMeetSum, we propose a novel multiple extractor guided summarization, namely Multi-DYLE, which extensively generalizes DYLE to enable using a supervised extractor based on human-aligned extractive oracles.We further present an explainabilityaware task, named "Explainable Evidence Extraction" (E3), which aims to automatically detect all evidence sentences that support a given summary.Experimental results on the QMSum dataset show that the proposed Multi-DYLE outperforms DYLE with gains of up to 3.13 in the ROUGE-1 score.We further present the initial results on the E3 task, under the settings using separate and joint evaluation metrics. 1