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Related Articles from SNS
Length Generalization Bounds for Transformers
Announce Type: replace Abstract: Length generalization is a key property of a learning algorithm that enables it to make correct predictions on inputs of any length, given finite training data. To provide such a guarantee, one needs to be able to compute a length generalization bound, beyond which the model is guaranteed to generalize. This paper concerns the open problem of the computability of such generalization bounds for C-RASP, a class of languages which is closely linked to transformers.
SmartThinker: Progressive Chain-of-Thought Length Calibration for Efficient Large Language Model Reasoning
arXiv:2603.08000v2 Announce Type: replace Abstract: Large reasoning models (LRMs) like OpenAI o1 and DeepSeek-R1 achieve high accuracy on complex tasks by adopting long chain-of-thought (CoT) reasoning paths. However, the inherent verbosity of these processes frequently results in redundancy and overthinking. To address this issue, existing works leverage Group Relative Policy Optimization (GRPO) to reduce LRM output length, but their static length reward design cannot dynamically adapt...
Algorithm for Contextual Queueing Bandits with Rate-Optimal Queue Length Regret
arXiv:2606.09668v1 Announce Type: new Abstract: Contextual queueing bandits provide a framework for learning to schedule heterogeneous jobs under unknown context-dependent service rates. Under stochastic contexts, existing algorithms achieve $\widetilde{\mathcal{O}}(T^{-1/4})$ queue length regret, defined as the expected difference between the learner's and oracle's queue lengths at horizon $T$. In this paper, we improve this rate to $\widetilde{\mathcal{O}}(T^{-1/2})$. The key observation...
Absolute Length Sensing in a Long-Baseline, High-Finesse Optical Cavity
arXiv:2606.09222v1 Announce Type: new Abstract: The relative phase between two lasers in transmission of an optical cavity can be used to continuously measure its absolute length with sub-micron precision. The first laser is kept on resonance with the cavity, while a second laser is phase-locked to the first with a frequency separation equal to an integer multiple of the cavity's initial free spectral range. As the free spectral range frequency changes due to cavity length changes, the...
The Choice of Line Lengths in Multiline Thru-Reflect-Line Calibration
Announce Type: replace-cross Abstract: This paper presents an analysis and rigorous procedure for determining the optimal lengths of line standards in multiline thru-reflect-line (TRL) calibration of vector network analyzers (VNAs). The solution is obtained through nonlinear constrained optimization of the eigenvalue problem in multiline TRL calibration. Additionally, we propose a simplified approach for near-optimal length selection based on predefined sparse rulers.
ReFLEX: Length-Generalizable CSI Denoising for MIMO-OFDM via Relative-Frequency Bias
arXiv:2606.00263v1 Announce Type: cross Abstract: This letter studies CSI denoising for MIMO--OFDM with variable NR resource block (RB) allocations. ReFLEX is a length-generalizable Transformer whose frequency attention uses a relative-frequency position bias (RFPB) generated from subcarrier offsets. A single checkpoint handles unseen RB lengths and can be applied to sparse DM-RS observations in the tested RB5/
HMPO: Hybrid Median-length Policy Optimization for Chain-of-Thought Compression
arXiv:2606.01934v1 Announce Type: new Abstract: Large language models achieve remarkable performance via extended chain-of-thought (CoT) reasoning, yet this lengthy process incurs substantial inference overhead. Existing CoT compression methods struggle with inflexible manual length budgets, computationally expensive multi-stage training pipelines, and fragile scalability restricted to small models. We propose HMPO (Hybrid Median-length Policy Optimization), a cost-effective, single-stage...
The length and time constants of propagating action potentials
Length and time constants are foundational to the study of conduction in neurons and other biological cables but are exactly defined only for passive membranes. Here we define and derive exact length and time constants for propagating action potentials in unmyelinated axons. This derivation exploits specific instants during action potential conduction when the net transmembrane ionic current is zero, but axial current remains non-zero.
On the Maximal Length of MDS Elliptic Codes
arXiv:2605.29439v2 Announce Type: replace Abstract: The determination of the maximal length of maximum distance separable (MDS) codes arising from elliptic curves is a central problem in coding theory. For an elliptic curve $E$ over $\mathbb{F}_q$, let $\operatorname{MEC}(k,q)$ denote the maximal length of a $q$-ary MDS elliptic code of dimension $k$. It was recently shown that $\operatorname{MEC}(k,q)\le\frac{q+1}{2}+\sqrt{q}$ for $q\ge289$ and $3\le k\le(q+1-2\sqrt{q})/10$, with equality...
DropSynth-Gold: Golden Gate Assembly in Emulsions Extends Multiplexed Gene Libraries to Greater Lengths
The ability to synthesize longer genes at scale remains a central challenge in multiplexed gene synthesis. DropSynth is a pooled gene synthesis platform that enables highly multiplexed, compartmentalized assembly from microarray-derived oligonucleotides, but current implementations rely on polymerase cycling assembly (PCA), which constrains fragment number, construct length, and assembly fidelity. Here we present DropSynth-Gold, an evolution of the DropSynth platform that replaces PCA with...