NC-Bench: An LLM Benchmark for Evaluating Conversational Competence

arXiv:2601.06426 · cs.CL, cs.AI · Submitted 2026-01-10 · Read on arXiv

cs.CL, cs.AI

Submitted: 2026-01-10

Updated: 2026-09-25

Code: https://github.com/IBM/nc-bench

Terminology

• RAG — 34× in this paper · explained in 3 episodes
• Benchmark — 28× in this paper · explained in 2 episodes
• RETRIEVAL-AUGMENTED GENERATION — 9× in this paper
• Retrieval-Augmented Generation (RAG) — 6× in this paper · explained in 16 episodes
• Accuracy — 3× in this paper · explained in 1 episode
• Benchmarking — 3× in this paper · explained in 3 episodes
• Fine-Tuning — 3× in this paper · explained in 5 episodes
• Grounding — 3× in this paper · explained in 3 episodes
• LLM-as-a-Judge — 3× in this paper · explained in 3 episodes
• Large Language Models (LLMs) — 2× in this paper · explained in 6 episodes
• Retrieval Augmented Generation (RAG) — 2× in this paper · explained in 4 episodes
• Adaptation — 1× in this paper · explained in 1 episode
• Adaptive Response — 1× in this paper · explained in 1 episode
• Alignment — 1× in this paper · explained in 1 episode
• Core — 1× in this paper · explained in 2 episodes
• Downstream Tasks — 1× in this paper · explained in 2 episodes
• Generative AI — 1× in this paper · explained in 2 episodes
• Grounded in the IBM Natural Conversation Framework — 1× in this paper
• Hallucination — 1× in this paper · explained in 3 episodes
• Regret — 1× in this paper · explained in 3 episodes

Sources

• Do Large Language Models Need Intent? Revisiting Response Generation Strategies for Service Assistant
• Benchmarking Large Language Models in Retrieval-Augmented Generation
• A Complete Survey on LLM-based AI Chatbots
• Survey of the State of the Art in Natural Language Generation: Core tasks, applications and evaluation
• The Llama 3 Herd of Models
• MTRAG: A Multi-Turn Conversational Benchmark for Evaluating Retrieval-Augmented Generation Systems
• LLMs Get Lost In Multi-Turn Conversation
• LaRA: Benchmarking Retrieval-Augmented Generation and Long-Context LLMs -- No Silver Bullet for LC or RAG Routing
• DailyDialog: A Manually Labelled Multi-turn Dialogue Dataset
• Zero-shot Conversational Summarization Evaluations with small Large Language Models
• Evaluating LLM Metrics Through Real-World Capabilities
• A Survey of the Evolution of Language Model-Based Dialogue Systems: Data, Task and Models
• Qwen2.5 Technical Report
• Does Model Size Matter? A Comparison of Small and Large Language Models for Requirements Classification
• A Comprehensive Analysis of the Effectiveness of Large Language Models as Automatic Dialogue Evaluators

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