Records found: 5
'Grok 4.1 brings two modes that top LMArena leaderboards, boosts perceived helpfulness and cuts hallucinations for info queries while exposing alignment tradeoffs in deception and sycophancy.'
'Ling 2.0 is a reasoning-first sparse MoE family from Ant Group that keeps per-token compute low with a 1/32 activation recipe while scaling from 16B to 1T parameters.'
'Google shows active learning can fine-tune LLMs with under 500 targeted labels, matching or improving model quality while reducing labeling needs by orders of magnitude.'
Internal Coherence Maximization (ICM) introduces a novel label-free, unsupervised training framework for large language models, achieving performance on par with human-supervised methods and enabling advanced capabilities without human feedback.
Researchers improve large language models' reasoning by explicitly aligning core abilities like deduction, induction, and abduction, surpassing traditional instruction-tuned models in accuracy and reliability.