LangMAP extends UnigramLM with language-specific MAP estimation, enabling multi-language tokenization from a shared vocabulary, improving morphological boundary alignment.

Clara Meister, Suchir Salhan, Andrzej Szablewski et al.

Proposes a dual-track framework combining rule engines and LLMs, boosting LaTeX template conversion fidelity and success rate.

Chung Cheuk Hei, Liu Li

DynamicMem introduces a long-horizon benchmark with 15-month synthetic user trajectories, evaluating multi-application memory and causal inference for personalized AI assistants.

Wenya Xie, Shengming Zhou, Zelin Li et al.

BLUEX v2 evaluates 21 LLMs on Brazilian second-phase exams, using multimodal, open-ended questions, with performance gap of 4.92 points.

João Guilherme Alves Santos, Giovana Kerche Bonás, Thiago Laitz et al.

Confident Layer Decoding dynamically selects the most reliable near-final layer to enhance reasoning in large language models.

Xuanming Zhang, Sining Zhoubian, Yuxuan Chen et al.

Hierarchical Transformer detects multi-turn jailbreaks with 0.9394 F1, outperforming baselines.

Chenhui Hu, Muhammed Salih, Sudipto Guha et al.

Proposed ViGiL3D++ combines scene graph sampling and LLM rephrasing to generate diverse 3D grounding descriptions, improving dataset richness.

Austin T. Wang, Dongchen Yang, Angel X. Chang

Proposes the nine-dimensional Meaning Intelligence Framework (MIF) to distinguish surface sentiment from true intent in Nigerian discourse; zero-shot accuracy 33.3%, schema-guided 73.3%.

Celestine Achi

Proposes a control-window law based on geometric cosine thresholds to predict single-neuron controllability, validated on 15 neurons with mean error 0.14.

Hongliang Liu

VeriBound explains FOVER-style transfer with PAC-Bayes theory, reaching 78.6% step verification accuracy.

Amirul Rahman, Mohammed Sabih Alsharari

Proposes Turing-RL, a reinforcement learning approach using discriminative Turing rewards to train human user simulators, outperforming traditional response matching methods.

Yingshan Susan Wang, Cedegao E. Zhang, Linlu Qiu et al.

Mining falsifiable research ideas from paper knowledge graphs using categorical structures, filtering ratio ~17:1.

Yuchen Wang, Zhongzhi Luan

Dango is a 1.8B-parameter L1-only model, using filtering to reduce L2 contamination, for studying L1-to-L2 transfer in SLA.

Shiho Matta, Yin Jou Huang, Fei Cheng et al.

Improved long-context reasoning using a data recipe and GRPO setup, achieving average gains of 7.2 points.

Xiaoyue Xu, Sikui Zhang, Xiaorong Wang et al.

RubricsTree constructs a hierarchical Boolean rubric system guided by expert-curated clinical criteria, enabling scalable, expert-aligned evaluation with over 100 atomic metrics, surpassing industry baselines.

Weizhi Zhang, Zechen Li, Hamid Palangi et al.

OPD-Evolver uses slow-fast on-policy distillation to learn memory selection, use, writing, and maintenance; its 9B model challenges 397B-scale systems.

Guibin Zhang, Xun Xu, Yanwei Yue et al.

Proposed OneModel internalizes complex business logic into a single model, reducing latency by 57.2% and increasing IRR from 64.3% to 83.3%.

Chang Liu, Chaoyang Ning, Dayi Jiang et al.

This study benchmarks 12 LLM pipeline configurations on MetaSyn, revealing a screening bottleneck with a maximum recall of 52.7% despite 90.9% retrieval recall at K=200.

Anzhe Xie, Weihang Su, Yujia Zhou et al.

Proposed audio-adapted Context-Aware Decoding (CAD) method enhances context adherence in spoken dialogue systems.

Che Hyun Lee, Heeseung Kim, Sungroh Yoon

SAG employs SQL-driven dynamic hyperedges, boosting multi-hop reasoning with 80% Recall@5 on MuSiQue, surpassing prior methods.

Yuchao Wu, Junqin Li, XingCheng Liang et al.