#training-objectives News & Analysis

2 articles tagged with #training-objectives. AI-curated summaries with sentiment analysis and key takeaways from 50+ sources.

2 articles

AIBullisharXiv – CS AI · Apr 157/10

🧠

How Transformers Learn to Plan via Multi-Token Prediction

Researchers demonstrate that multi-token prediction (MTP) outperforms standard next-token prediction (NTP) for training language models on reasoning tasks like planning and pathfinding. Through theoretical analysis of simplified Transformers, they reveal that MTP enables a reverse reasoning process where models first identify end states then reconstruct paths backward, suggesting MTP induces more interpretable and robust reasoning circuits.

AINeutralarXiv – CS AI · Apr 146/10

🧠

LLMs Should Incorporate Explicit Mechanisms for Human Empathy

Researchers argue that Large Language Models lack explicit empathy mechanisms, systematically failing to preserve human perspectives, affect, and context despite strong benchmark performance. The paper identifies four recurring empathic failures—sentiment attenuation, granularity mismatch, conflict avoidance, and linguistic distancing—and proposes empathy-aware objectives as essential components of LLM development.