Decoupling Generation and Selection for Budget-Constrained Faithful Summarization

arXiv:2608.03655 · cs.CL, cs.AI · Submitted 2026-08-04 · Read on arXiv

Zeyu Wang, Guanghua Wang, Meng Xu

cs.CL, cs.AI

Submitted: 2026-08-04

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Redundancy — 37× in this paper · explained in 2 episodes
• Consistency — 28× in this paper · explained in 3 episodes
• Faithfulness — 27× in this paper · explained in 2 episodes
• Grounding — 22× in this paper · explained in 3 episodes
• Generator — 19× in this paper · explained in 2 episodes
• Abstractive Summarization — 18× in this paper · explained in 1 episode
• Benchmark — 18× in this paper · explained in 2 episodes
• Hallucination — 18× in this paper · explained in 4 episodes
• Papers — 17× in this paper · explained in 3 episodes
• Clarity — 8× in this paper · explained in 3 episodes
• Coherence — 8× in this paper · explained in 2 episodes
• Decoder — 5× in this paper · explained in 2 episodes
• Decoupling — 5× in this paper · explained in 2 episodes
• Semantic Similarity — 4× in this paper · explained in 2 episodes
• Combinatorial Optimization — 3× in this paper · explained in 2 episodes
• Scoring Function — 3× in this paper · explained in 2 episodes
• Active Learning — 2× in this paper · explained in 6 episodes
• Benchmarking — 2× in this paper · explained in 4 episodes
• Contrastive Learning — 2× in this paper · explained in 9 episodes
• Embeddings — 2× in this paper · explained in 2 episodes
• Evaluation Protocol — 2× in this paper · explained in 2 episodes
• Instruction Tuning — 2× in this paper · explained in 3 episodes
• Model-Agnostic — 2× in this paper · explained in 2 episodes
• Positional Bias — 2× in this paper · explained in 2 episodes
• Self-Consistency — 2× in this paper · explained in 3 episodes
• Ablation — 1× in this paper · explained in 1 episode
• Computational overhead — 1× in this paper · explained in 2 episodes
• Elias — 1× in this paper · explained in 2 episodes
• Generalization — 1× in this paper · explained in 14 episodes
• In-Context Learning — 1× in this paper · explained in 7 episodes
• Language Models (LLMs) — 1× in this paper · explained in 2 episodes
• Large Language Models (LLMs) — 1× in this paper · explained in 9 episodes
• Modularity — 1× in this paper · explained in 9 episodes
• Mutual Information — 1× in this paper · explained in 2 episodes
• Position Bias — 1× in this paper · explained in 2 episodes
• Regularization — 1× in this paper · explained in 3 episodes
• Semantic Alignment — 1× in this paper · explained in 6 episodes
• Tokenization — 1× in this paper · explained in 2 episodes
• Transformer — 1× in this paper · explained in 2 episodes
• Transformers — 1× in this paper · explained in 2 episodes
• Verification — 1× in this paper · explained in 2 episodes

Sources

• FABLES: Evaluating faithfulness and content selection in book-length summarization
• Qwen3.5-Omni Technical Report
• BERTScore: Evaluating Text Generation with BERT

Related papers

• Exploring Solution Divergence and Its Effect on Large Language Model Problem Solving
• Ishigaki-IDS-Bench: A Benchmark for Generating Information Delivery Specification from BIM Information Requirements
• Subliminal Steering: Stronger Encoding of Hidden Signals
• MedStruct-S: A Benchmark for Key Discovery, Key-Conditioned QA and Semi-Structured Extraction from OCR Clinical Reports
• The End of Transformers? On Challenging Attention and the Rise of Sub-Quadratic Architectures
• Untangling the Mechanisms of Misleading Context in Medical Question Answering