20 papers · ranked by Valyu relevance
Ye Fan, Jidong Ge, Chuanyi Li, Liguo Huang + 1 more
While pre-trained models have achieved remarkable success in code search, their multilingual capabilities remain a major hurdle, plagued by data imbalance, cross-lingual semantic interference, and the loss of critical information from existing unified representations like Abstract Syntax Trees (ASTs) or Intermediate…
Alix Petit, Aida Koch, Logan Lewis, Lily Scott
Universal coders process individual sequences without assuming that the source distribution is known. In this setting, uniformly generated sequences represent the most difficult test case: the source simulates pure randomness, contains no exploitable bias, and forces a frequency-estimating universal coder to infer the…
Nicholas J. C. Papadopoulos, Ramin Ayanzadeh
Fault-tolerant quantum computation allows quantum computations to be carried out while resisting unwanted noise. Several error-correcting codes have been developed to achieve this task, but none alone are capable of universal quantum computation. This universality is highly desired and often achieved using additional…
Sawsan Wehbi, Nhan Ly-Trong, Andrew Wheeler, Bui Quang Minh + 2 more
We evaluate whether tryptophan (W), widely thought to be the last of the 20 canonical amino acids added to the genetic code, was already present in the Last Universal Common Ancestor (LUCA). We reconstruct the evolutionary history of tryptophanyl-tRNA synthetase (WRS), the enzyme that attaches W to its tRNA, and the…
Jingwen Liu, Alexandr Andoni, Daniel Hsu
We introduce \emph{universal transformers}: fixed transformers that can simulate any transformer in a given class via a suitable input embedding. Analogous to a universal Turing machine, the input embedding encodes a description of the target model while all internal parameters remain fixed. We provide explicit sparse…
Junhao Chen, Jingxuan Zhang, Jian He, Yixuan Tang + 1 more
The lexical and syntactic disparities among different programming languages (e.g., Java and Python) pose significant challenges for multi-language software engineering tasks such as cross-language code clone detection and code retrieval, since queries or code snippets written in one programming language often fail to…
Ezequiel López-Rubio
The reflected binary Gray code arranges the fixed-length binary representations of the integers so that consecutive numbers differ in a single bit. Its usefulness, however, is tied to a fixed word length $b$, which both caps the range of representable numbers at $2^{b}-1$ and wastes bits on small integers. We introduce…
Yosef Akhtman, Boris Ryabko
We propose a unified mathematical framework showing that the representational universality of modern foundational models arises from a shared finite latent domain. Building on the Finite Ring Continuum (FRC) framework, we model all modalities as epistemic projections of a common latent set $Z\subsetU_{t}$, where…
Alessandro Achille, Stefano Soatto, Ming Li
We describe AI agents as stochastic dynamical systems and frame the problem of learning to reason as in transductive inference: Rather than approximating the distribution of past data as in classical induction, the objective is to capture its algorithmic structure so as to reduce the time needed to solve new tasks. In…
Huanqiu Zhang, Israel Nelken, Tatyana Sharpee
Deciphering the neural code requires identifying its fundamental symbols or code-words. Neural activity is usually interpreted either as a rate code – based on average spike counts – or as a temporal code, which distinguishes patterns with identical counts. Yet, the symbols of the code remain undefined. Here we show…
Authors not listed
This comprehensive review examines the evolution of autonomous materials synthesis laboratories that integrate artificial intelligence with advanced robotics to accelerate discovery. Traditional materials development pipelines typically require 10-20 years, but self-driving laboratories (SDLs) and Materials…
Eduardo Y. Sakabe, Felipe S. Abrahão, Alexandre Simões, Esther Colombini + 3 more
Understanding and controlling the complexity of neural networks is a central challenge in machine learning, with implications for generalization, optimization, and model capacity. While most approaches rely on entropy-based loss functions and statistical metrics, these measures often fail to capture deeper, causally…
Yanshuo Chen, Yuming Zhang, Joshua Li, Boxue Tian + 1 more
Codon optimization involves selecting synonymous codons to match host-specific preferences. It is critical for heterologous expression but remains challenging due to the combinatorial design space. Under long-term evolutionary selection, natural coding sequences are near-optimal compromises between translational…
Neri Merhav, Chi Wan Sung
We derive a few extended versions of the Kraft inequality for information lossless finite-state encoders. The main basic contribution is in defining a notion of a Kraft matrix and in establishing the fact that a necessary condition for information losslessness of a finite-state encoder is that none of the eigenvalues…
Daisuke Tsugama, Kota Kambara
Codon usage determines gene expression levels, yet its universal principles remain elusive. Here, we developed a regression-based model to derive “codon weights” from transcriptomic data, enabling improved prediction of mRNA and protein abundance across diverse taxa, including plants, mammals, insects, and microbes.…
Lihong Cao
The human brain encodes a virtually infinite repertoire of semantic concepts using a finite number of neurons, a feat that defies the capacity limits of classical attractor networks. While “Concept Cells” in the medial temporal lobe (MTL) exhibit extreme sparsity, the information-theoretic principles governing their…
Florian P. Mahner, Johannes Roth, Ka Chun Lam, Michael F. Bonner + 2 more
Deep neural networks trained with different architectures, objectives, and datasets have been reported to converge on similar visual representations. However, what remains unknown is which visual properties models actually converge on and which factors may underlie this convergence. To address this, we decompose the…
Authors not listed
Sequence-defined oligomers offer programmable molecular architectures with potential in data storage, authentication, and anticounterfeiting. However, their deployment in real-world materials has been constrained by their low scale, limited thermal resilience and the need for specialized analytical methods. Here we…
Zoe Leyva-Acosta, Eduardo Acuña Yeomans, Francisco Hernández-Quiroz, Ming Li
Algorithmic complexity is a foundational notion in theoretical computer science, but its incomputability has led to two families of practical estimators: compression-based and program-execution-based (e.g., the Coding Theorem Method, CTM). Despite widespread use, the correspondence between these paradigms remains…
Tuomo Kiiskinen, Oscar Kivinen, Manuel A Rivas
The central problem of biology is the origin of biological organization. We show, using information theory, that an organism does not contain enough organism-specific information to specify its own fully functioning microscopic organization. The organized machinery of life is therefore not the execution of a fully…