iFlip: Iterative Feedback-driven Counterfactual Example Refinement

arXiv:2601.01446 · cs.CL, cs.LG · Submitted 2026-01-04 · Read on arXiv

cs.CL, cs.LG

Submitted: 2026-01-04

Updated: 2026-08-26

Terminology

• Iterative Refinement — 29× in this paper · explained in 3 episodes
• Ablation — 14× in this paper · explained in 1 episode
• LLM-as-a-Judge — 13× in this paper · explained in 3 episodes
• Transferability — 13× in this paper · explained in 4 episodes
• Data Augmentation — 11× in this paper · explained in 7 episodes
• Label Flipping Rate — 11× in this paper
• Robustness — 10× in this paper · explained in 5 episodes
• Semantic Similarity — 9× in this paper · explained in 2 episodes
• Counterfactual Data Augmentation — 8× in this paper
• Perplexity — 6× in this paper · explained in 3 episodes
• Ablation Studies — 5× in this paper · explained in 1 episode
• Ablation study — 5× in this paper · explained in 1 episode
• Accuracy — 5× in this paper · explained in 1 episode
• Alignment — 5× in this paper · explained in 1 episode
• Adam — 4× in this paper · explained in 2 episodes
• Empirical Methods in Natural Language Processing — 4× in this paper
• Explainability — 4× in this paper · explained in 3 episodes
• Transformer — 4× in this paper · explained in 2 episodes
• Benchmark — 3× in this paper · explained in 2 episodes
• Core — 3× in this paper · explained in 2 episodes
• Fidelity — 2× in this paper · explained in 2 episodes
• Interpretability — 2× in this paper · explained in 15 episodes
• Large Language Models (LLMs) — 2× in this paper · explained in 6 episodes
• Adversarial Examples — 1× in this paper · explained in 2 episodes
• Agentic Framework — 1× in this paper · explained in 6 episodes
• Benchmarking — 1× in this paper · explained in 3 episodes
• Consistency — 1× in this paper · explained in 3 episodes
• Contrastive Learning — 1× in this paper · explained in 5 episodes
• Cosine Similarity — 1× in this paper · explained in 3 episodes
• Downstream Tasks — 1× in this paper · explained in 2 episodes
• Embeddings — 1× in this paper · explained in 2 episodes
• Generalizability — 1× in this paper · explained in 6 episodes
• LLM judge — 1× in this paper · explained in 2 episodes
• Quantization — 1× in this paper · explained in 12 episodes
• Reinforcement Learning — 1× in this paper · explained in 4 episodes
• Verification — 1× in this paper · explained in 2 episodes
• alpha — 1× in this paper · explained in 1 episode

Sources

• Large Language Monkeys: Scaling Inference Compute with Repeated Sampling
• DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning
• On the Intrinsic Self-Correction Capability of LLMs: Uncertainty and Latent Concept
• The Llama 3 Herd of Models
• A Survey on LLM-as-a-Judge
• Confidence-Guided Error Correction for Disordered Speech Recognition
• A Comparative Analysis of Counterfactual Explanation Methods for Text Classifiers
• Not Just a Black Box: Learning Important Features Through Propagating Activation Differences
• Gemma 3 Technical Report
• 2 OLMo 2 Furious
• gpt-oss-120b & gpt-oss-20b Model Card
• Self-Correcting Large Language Models: Generation vs. Multiple Choice
• Through a Compressed Lens: Investigating The Impact of Quantization on Factual Knowledge Recall
• Qwen3 Technical Report

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