TRACE, a novel dense credit-assignment framework for reinforcement learning, dramatically improved agent performance on the BrowseComp-Plus benchmark, boosting Qwen3-4B from 7.2 to 35.6 and Qwen3-30B-…
Frontier AI models can rediscover 61.25% of known legal loopholes and generate new ones, according to a study by Wei Liu et al. in 'Large Language Models Hack Rewards, and Society,' raising concerns t…
A new method called UMoE realigns Mixture-of-Experts (MoE) models to enhance domain-specific performance without increasing expert count, parameters, or inference cost. Across Qwen3-30B-A3B and Qwen3.…
Stanford researchers introduced TRACE, an open-source system that diagnoses recurring agent failures and trains targeted capabilities via synthetic reinforcement learning environments, achieving a hig…
Researchers at ACL 2026 introduced a method to reuse LLM hidden states for classification tasks, training lightweight probes on token- and layer-selective representations to eliminate separate guard m…
Alibaba's Qwen team released Qwen3-30B-A3B, a Mixture-of-Experts model with 30.5 billion total parameters but only 3.3 billion active per token, enabling it to run on a single 24 GB graphics card at s…
Researchers propose a structural pruning framework for Mixture-of-Experts (MoE) models that reformulates prune-ratio allocation as a channel-score coverage maximization problem, solved via attribution…
A systematic human audit of the NL-to-FOL benchmarks FOLIO and MALLS found that approximately 39% and 36% of entries, respectively, contain incorrect FOL formalizations, with additional errors in ambi…