Response Generation
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Benchmarks
Most implemented
Language Models are Unsupervised Multitask Learners
A Diversity-Promoting Objective Function for Neural Conversation Models
Unified Language Model Pre-training for Natural Language Understanding and Generation
NLG Evaluation Metrics Beyond Correlation Analysis: An Empirical Metric Preference Checklist
MASS: Masked Sequence to Sequence Pre-training for Language Generation
Papers
Can Computation from Earlier Problems Help LLMs Solve New Ones?
Large language models often solve independent problems in the same conversation. Can computation from earlier problems help them solve new ones? To answer this question, we first conduct preliminary experiments showing t…
Response GenerationAct First, Reason Later: Accelerating On-Policy Distillation for Multi-Turn Agents via Reference-Conditioned Inverse Dynamics
On-policy distillation (OPD) trains multi-turn language agents with dense teacher supervision on student-generated responses. However, standard think-then-act rollouts require lengthy reasoning before each short action, …
Response GenerationMOCC-R1: Reinforcing Reasoning-Response Consistency for Multimodal Counselor Response Generation
Multimodal counselor response generation (MCRG) aims to generate an appropriate counselor response from multimodal dialogue histories. Progress is limited by two gaps: first, existing datasets rarely capture sustained, h…
Reinforcement LearningResponse GenerationControlling and Assessing Appropriate Persona Use in LLM-based Dialogue Generation
In persona-based dialogue generation (PDG), LLMs often overuse persona attributes by incorporating them regardless of dialogue context, resulting in unnatural responses. Despite its practical significance, the underlying…
Response GenerationDialogue GenerationMulti-Modal Semantic Expansion with Constrained LLM Reranking for Conversational Music Recommendation
We present Team Semiintelligencn's solution for the ACM RecSys 2026 TalkPlayData Challenge, addressing conversational music recommendation through a multi-modal and personalized conversational recommender system. Our sub…
Response GenerationA knowledge-guided agentic framework for mitigating patient-context ambiguity in health queries
Patients often submit short, underspecified queries to healthcare chatbots that lack the patient-specific information needed to determine an appropriate response. Although these queries may be linguistically clear, they …
Response Generation