title: Can a Single Model Master Both Multi-turn Conversations and Tool Use?
    CALM: A Unified Conversational Agentic Language Model
summary: Large Language Models (LLMs) with API-calling capabilities enabled building
  effective Language Agents (LA), while also revolutionizing the conventional
  task-oriented dialogue (TOD) paradigm. However, current approaches face a
  critical dilemma: TOD systems are often trained on a limited set of target
  APIs, requiring new data to maintain their quality when interfacing with new
  services, while LAs are not trained to maintain user intent over multi-turn
  conversations. Because both robust multi-turn management and advanced function
  calling are crucial for effective conversational agents, we evaluate these
  skills on three popular benchmarks: MultiWOZ 2.4 (TOD), BFCL V3 (LA), and
  API-Bank (LA), and our analyses reveal that specialized approaches excel in one
  domain but underperform in the other. To bridge this chasm, we introduce CALM
  (Conversational Agentic Language Model), a unified approach that integrates
  both conversational and agentic capabilities. We created CALM-IT, a carefully
  constructed multi-task dataset that interleave multi-turn ReAct reasoning with
  complex API usage. Using CALM-IT, we train three models CALM 8B, CALM 70B, and
  CALM 405B, which outperform top domain-specific models, including GPT-4o,
  across all three benchmarks.
paper_authors._id: 67aece59f2e8a2ee35b5affd
paper_authors.name: Emre Can Acikgoz
paper_authors.status: claimed_verified
paper_authors.statusLastChangedAt: 2025-02-18T09:34:01.421Z
paper_authors._id: 63888d3fd68e37abd599f428
paper_authors.avatarUrl: https://cdn-avatars.huggingface.co/v1/production/uploads/63888d3fd68e37abd599f428/YaNyxG_oM6IgrHTkFZ6Eq.jpeg
paper_authors.fullname: emre can
paper_authors.type: user
paper_authors.user: emrecanacikgoz
paper_authors._id: 67aece59f2e8a2ee35b5affe
paper_authors.name: Jeremiah Greer
paper_authors._id: 67aece59f2e8a2ee35b5afff
paper_authors.name: Akul Datta
paper_authors._id: 67aece59f2e8a2ee35b5b000
paper_authors.name: Ze Yang
paper_authors._id: 67aece59f2e8a2ee35b5b001
paper_authors.name: William Zeng
paper_authors._id: 67aece59f2e8a2ee35b5b002
paper_authors.name: Oussama Elachqar
paper_authors._id: 67aece59f2e8a2ee35b5b003
paper_authors.name: Emmanouil Koukoumidis
paper_authors._id: 67aece59f2e8a2ee35b5b004
paper_authors.name: Dilek Hakkani-Tür
paper_authors._id: 67aece59f2e8a2ee35b5b005
paper_authors.name: Gokhan Tur
paper_title: Can a Single Model Master Both Multi-turn Conversations and Tool Use?
    CALM: A Unified Conversational Agentic Language Model
paper_summary: Large Language Models (LLMs) with API-calling capabilities enabled building
  effective Language Agents (LA), while also revolutionizing the conventional
  task-oriented dialogue (TOD) paradigm. However, current approaches face a
  critical dilemma: TOD systems are often trained on a limited set of target
  APIs, requiring new data to maintain their quality when interfacing with new
  services, while LAs are not trained to maintain user intent over multi-turn
  conversations. Because both robust multi-turn management and advanced function
  calling are crucial for effective conversational agents, we evaluate these
  skills on three popular benchmarks: MultiWOZ 2.4 (TOD), BFCL V3 (LA), and
  API-Bank (LA), and our analyses reveal that specialized approaches excel in one
  domain but underperform in the other. To bridge this chasm, we introduce CALM
  (Conversational Agentic Language Model), a unified approach that integrates
  both conversational and agentic capabilities. We created CALM-IT, a carefully
  constructed multi-task dataset that interleave multi-turn ReAct reasoning with
  complex API usage. Using CALM-IT, we train three models CALM 8B, CALM 70B, and
  CALM 405B, which outperform top domain-specific models, including GPT-4o,
  across all three benchmarks.
paper_ai_keywords: Large Language Models (LLMs) API-calling capabilities Language Agents (LA) task-oriented dialogue (TOD) MultiWOZ 2.4 BFCL V3 API-Bank multi-turn management CALM (Conversational Agentic Language Model) CALM-IT multi-task dataset ReAct reasoning CALM 8B CALM 70B CALM 405B GPT-4o