1 citations · 2 across the 15 of their papers we have counts for
7 papers · 1 filter
Thinking Seeds: Restarting On-Policy RL from the Model's Own Past Reasoning States
Lei Yang, Wei Bi, Chenxi Sun +2
On-policy reinforcement learning (RL) for language models trains on the reasoning states visited by the current policy. As training sharpens the policy, some states reached by earl…
Compass-Embedding v4: Robust Contrastive Learning for Multilingual E-commerce Embeddings
Pakorn Ueareeworakul, Shuman Liu, Jinghao Feng +7
As global e-commerce rapidly expands into emerging markets, the lack of high-quality semantic representations for low-resource languages has become a decisive bottleneck for retrie…
LongCat-Flash Technical Report
Meituan LongCat Team, Bayan, Bei Li +179
We introduce LongCat-Flash, a 560-billion-parameter Mixture-of-Experts (MoE) language model designed for both computational efficiency and advanced agentic capabilities. Stemming f…
What is an "Abstract Reasoner"? Revisiting Experiments and Arguments about Large Language Models
Tian Yun, Chen Sun, Ellie Pavlick
Recent work has argued that large language models (LLMs) are not "abstract reasoners", citing their poor zero-shot performance on a variety of challenging tasks as evidence. We rev…
How new data permeates LLM knowledge and how to dilute it
Chen Sun, Renat Aksitov, Andrey Zhmoginov +5
Large language models learn and continually learn through the accumulation of gradient-based updates, but how individual pieces of new information affect existing knowledge, leadin…
Learning and Unlearning of Fabricated Knowledge in Language Models
Chen Sun, Nolan Andrew Miller, Andrey Zhmoginov +2
What happens when a new piece of knowledge is introduced into the training data and how long does it last while a large language model (LM) continues to train? We investigate this…
Evaluating the Generation Capabilities of Large Chinese Language Models
Hui Zeng, Jingyuan Xue, Meng Hao +3
This paper unveils CG-Eval, the first-ever comprehensive and automated evaluation framework designed for assessing the generative capabilities of large Chinese language models acro…