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3,629 papers
This work empirically study the potential of outer prefixes, revealing the mechanism of the impact of distributional discrepancy to the exploration dynamics in RLVR training and efficiently mitigates entropy collapse without requiring additional SFT, intricate reward designs, or complex prompting.
This work shows that $\beta$ entangles two distinct roles: it governs the effective inverse preference-noise scale and simultaneously rescales the optimization dynamics, coupling this scale with the effective step size, and proposes a centered-softplus reformulation that is argmin-equivalent to DPO for $\beta>0$, while...
Experimental results show that CritICL consistently outperforms standard in-context learning and achieves performance competitive with or superior to test-time scaling methods, while requiring significantly fewer generations and lower token cost.
Large-scale, standardized datasets have driven many advances in AI-based scientific modeling, from protein structure prediction to natural language processing. Infectious disease epidemiology is increasingly adopting AI methods for forecasting, surveillance, and outbreak analytics, but the time-series data available to...
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This work introduces Visual Retrieval Heads (VRHs), a small subset of attention heads that are causally responsible for grounding text descriptions to image regions, and shows that scoring attention from output prediction tokens with a sum over the ground-truth referent region most reliably identifies causal heads.
This report presents an open pretraining recipe that trains a collection of Puro-2B models from scratch on up to 1.4 trillion tokens with FP8 precision on consumer-grade RTX 5090 GPUs, and derives a Puro Cost Scaling Law that relates training cost to average model performance.
This study provides a systematic comparison of several open-source LLMs on a structured intestinal symptom extraction task and concludes that Qwen3 models offer a favorable balance between accuracy and efficiency, making them suitable for resource-constrained scenarios.
CMPM, a Chinese Multi-Panel Meme benchmark with 1,214 annotated samples covering five structural types, ordering dependency, panel-order constraints, and optional comment context, is introduced and results indicate that canonical-display accuracy is not by itself evidence of order understanding.
FLARE is proposed, a novel framework that endows VLAs with robust error recovery capabilities through a ``Retry" and ``Reset" Paradigm, and significantly improves task success and robustness.
The effect of introducing the manager-worker scaffold over a shared filesystem workspace, with no training and no per-benchmark tuning, measured against the same model answering in a single pass is investigated, finding several mechanisms behind the gains.
This paper presents Ankhdjet, an open-source compiler that lowers a HuggingFace ternary checkpoint to a via-mask program of a fixed compute-in-ROM macro on the open SKY130 PDK, verified end to end with open tools.
BekchiAI is a complementary web-based observability and control layer for deployed agents, providing full token and latency telemetry as well as remote run termination and the benchmark, evaluation tools, and platform are publicly released.
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