Papers Response Generation
“Response Generation” 태그가 달린 논문 1,118편 · 필터 해제
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 GenerationDentAgent: Evidence-Centric Multi-Agent Coordination for Multimodal Dental Reasoning
Oral diseases affect billions of people worldwide, underscoring a pressing need for accurate and reliable dental assessment that integrates heterogeneous evidence from domain knowledge, radiographs, intraoral photographs…
Response GenerationQuestion AnsweringClosing the Affective Loop: Multimodal Speaker-Listener Emotion-Dynamics-Aware Empathetic Social Robots
Empathetic social robots should respond not only to what users say, but also to how their emotions dynamically evolve during interaction. However, existing empathetic dialogue systems are often text-centered and primaril…
Response GenerationQUMem: Personalized Memory for Query-Conditioned User-State Inference in LLM Agents
Large language model (LLM) agents increasingly use external memory systems to support personalization by drawing on long and evolving interaction histories, in which user preferences may be distributed across time, chang…
Response GenerationTowards Robust Tool Use in Agents via Experience-Driven Adaptive Guidance
The performance bottleneck of agents is increasingly shifting from model capability to the robustness of their execution processes. Tools play a central role as the primary interface through which agents interact with ex…
Response GenerationCognivia: A Cognitive Behavioral Therapy Copilot for Evidence-Based Mental Healthcare
Cognitive distortion amplifies negative emotions and contributes to mental health disorders. Cognitive Behavioral Therapy (CBT) is an effective way to address cognitive distortions, but its large-scale application is lim…
Response GenerationToward Anthropomorphic Dialogue: A Closed-Loop Framework for Human-Like Chat Generation, Evaluation, and Preference Alignment
Human-like private chat requires more than fluent response generation: a system must preserve persona, relationship, memory, bounded knowledge, medium-specific timing, and a coherent multi-turn arc. We present AnthroDial…
Response GenerationEnjoy Your Talk: A Human-Centered Benchmark for Multi-Turn Dialogue with Decoupled User Simulation, Target Modeling, and Judging
Evaluating large language models (LLMs) as multi-turn conversational partners requires probing capabilities that single-turn benchmarks miss: persona consistency, evolving intent tracking, emotional dynamics, and goal co…
Response GenerationDialogue EvaluationMedRealMM: A Real-World Multimodal Benchmark for Chinese Online Medical Consultation
Large language models (LLMs) are increasingly deployed in online medical consultation, yet existing benchmarks remain poorly aligned with real clinical practice. Many rely on synthetic conversations or patient simulators…
Response GenerationUncovering Salience-Driven Dynamics in Consumer Confidence with Generative Social Simulation
Consumer confidence is typically modeled as a persistent macroeconomic index, yet its movements arise from households that interpret economic information through heterogeneous constraints, exposures, prior beliefs, and a…
Response GenerationTraining Therapeutic Judges and Multi-Agent Systems for Human-Aligned Mental Health Support
Large language models show promise for mental health support, yet therapeutic quality improves only when evaluation functions as an actionable control signal rather than a passive metric. We introduce a framework that fo…
Response GenerationMIThinker: A Plug-and-Play Policy-Optimized Thinker For Motivational Interviewing Counseling
Reasoning large language models (LLMs) have recently made much progress in complex problem-solving, leveraging internal reasoning (or thought) to guide their solution generation. However, existing LLM-based counseling ag…
Reinforcement LearningResponse GenerationSHIFT: Gate-Modulated Activation Steering for Knowledge Conflict Mitigation in Retrieval-Augmented Generation
Retrieval-augmented generation (RAG) enhances LLMs by incorporating external knowledge to support response generation. However, conflicts between retrieved context and parametric knowledge have emerged as a critical chal…
Response GenerationConstraint Tax in Open-Weight LLMs: An Empirical Study of Tool Calling Suppression Under Structured Output Constraints
Tool Calling and Structured Output are two core capabilities of modern Agent systems, yet their interaction under joint deployment conditions remains insufficiently understood. This paper reports a reproducible phenomeno…
Response GenerationDziri Voicebot: An End-to-End Low-Resource Speech-to-Speech Conversational System for Algerian Dialect
Automatic speech and language technologies are still heavily biased toward high-resource languages, limiting their applicability to dialectal and low-resource settings such as Algerian Dialect. This language presents add…
Natural Language UnderstandingText-To-Speech SynthesisIntent ClassificationResponse Generation