docs: add KTO (2402.01306) to Paper Index + link ref to KTOTrainer (#4440)

Co-authored-by: Quentin Gallouédec <gallouedec.quentin@gmail.com>
Co-authored-by: Quentin Gallouédec <45557362+qgallouedec@users.noreply.github.com>

Author: SSusantAchary

docs/source/paper_index.md

@@ -479,6 +479,33 @@ training_args = DPOConfig(
 
 These parameters only appear in the [published version](https://aclanthology.org/2025.tacl-1.22.pdf)
 
+## Kahneman–Tversky Optimization
+
+Papers relating to the [`KTOTrainer`]
+
+### KTO: Model Alignment as Prospect Theoretic Optimization
+
+**📜 Paper**: https://huggingface.co/papers/2402.01306
+
+KTO derives an alignment objective from prospect theory and learns directly from **binary** human feedback (liked/disliked), matching or surpassing DPO-style methods while handling imbalanced/noisy signals well.
+To reproduce the paper's setting, you can use the default configuration of [`KTOTrainer`]:
+
+```python
+from trl import KTOConfig, KTOTrainer
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model = AutoModelForCausalLM.from_pretrained(model_id)
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+
+trainer = KTOTrainer(
+    model=model,
+    processing_class=tokenizer,
+    args=KTOConfig(),
+    train_dataset=...,
+)
+trainer.train()
+```
+
 ## Supervised Fine-Tuning
 
 Papers relating to the [`SFTTrainer`]