This work proposes StrategyBench, which selects strategy-inducible tasks from BIG-Bench, constructs reference strategies, and defines evaluation metrics along two dimensions: strategy quality and downstream utility, and experiments show that explicit strategy utility differs substantially across task categories and dep...
Jing-Han Tan, Yuanzhe Wang, Lu Chen et al.· 0 citations
Green-patent indicators based on Cooperative Patent Classification Y02 tags increasingly inform research, industrial policy, and climate-oriented investment, yet their construct validity has not been evaluated at corpus scale. We ask whether Y02 classification errors are random measurement noise or systematic, directio...
Hamid Bekamiri, Jan Auernhammer, Milad Abbasiharofteh et al.· 0 citations
We present HelaBERT, a family of two BERT-based masked language models pre-trained from scratch on approximately 1 billion tokens of Sinhala text sourced from MADLAD-400, CulturaX, and a custom corpus comprising news articles, Sinhala Wikipedia, and web crawl data. HelaBERT-Small (~23.3M parameters, 6 layers) and HelaB...
An audit is introduced that predicts a mechanism's fate as a population grows, asking how often the mechanism can act, whether agents use the information it supplies, and whether the measurement itself creates apparent scale effects.
Zeng-Qing Wu, Chuan Xiao· 0 citations
Reach audiences
Advertise in front of researchers, engineers, and readers.
A solver-informed diagnosis mechanism that exploits fine-grained solver statistics as verbal gradients for targeted refinement and a structured memory abstracts prior experience into reusable modeling strategies, avoiding redundant exploration while enabling zero-shot transfer to unseen problems and bootstrapping small...
Haofeng Yuan, Jianing Peng, Jieyi Bi et al.· 0 citations
A reproducible, license-aware knowledge-distillation recipe addressing the constraint of deploying a safety layer for large language models on commodity hardware by partitioning the corpus into seven safety categories aligned to a public hazard taxonomy.
Edson Rodrigues da Cruz, Paulo Ricardo Ferreira Neves, P. H. Falsetti et al.· 0 citations
Website redundancy does not have a single fixed meaning. The same repeated element may distract during one task and provide backup during another. We introduce CORA (Counterfactual, Observable Redundancy Audit), which measures repetition load, normal-use tax, and failure-domain recovery reserve separately. Each run ret...
KFS-RAG is proposed, a defense that mitigates information leakage by reformulating the retrieved context by identifying a small set of influential keywords from the retrieved context via an attention rollout plus a causal perturbation mechanism.
Ziliang Zhang, Yu-Bo Zhu, Wei Tong et al.· 0 citations
A unified framework is introduced that distills intermediate representations that explicitly encode the physical modeling process and adopt a two-stage post-training strategy, where supervised fine-tuning establishes structured modeling, and reinforcement learning with rubric-based feedback improves the quality of the...
Ye Zhang, Xue-Hang Guo, Rui Pan et al.· 1 citation
PUMA (Polish Unified Multimodal Assessment) is proposed, a novel benchmark of 900 hand-crafted tasks designed to probe the limits of multimodal models in the Polish cultural and linguistic context and open-source the evaluation framework to advance localized multimodal AI research.
Slawomir Dadas, Michał Perełkiewicz, Rafal Poswiata et al.· 0 citations
This work sweeps a 64-shape matrix of LLM primitives that varies how a computation is expressed while holding what it computes fixed, recording per-operation device support and finds that placement is a property of how a computation is expressed, not of what it computes.
This work presents the most comprehensive evaluation of LLM safety capabilities to date, systematically testing models across datasets that are organized into four distinct categories, and uncovers critical blind spots.