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Related Articles from SNS

How Far Can Chord-Symbol Time-Series Adaptation Carry Genre Identity? Capabilities and Boundaries in Multi-Genre Chord-Symbol Modeling

Announce Type: new Abstract: Harmony is a compact symbolic layer where mathematical pitch relations, acoustic consonance, and musical convention meet. This report treats chord-symbol sequences not as a complete representation of music, but as an interpretable, controllable time series for genre-local harmonic modeling. Starting from a frozen pop-jazz Music Transformer checkpoint, I evaluate how far small adaptation interfaces can extend the model to eleven target genres: blues, bossa nova,...

arXiv CS 2d ago

A Data-Free Symbolic Regression Approach for Solving Equations

arXiv:2606.07152v1 Announce Type: new Abstract: Many equations arising in science currently cannot be solved by available analytical techniques and are therefore solved numerically, without yielding explicit symbolic expressions. Existing symbolic regression approaches can recover symbolic expressions, but require training data obtained from the underlying process, rather than the governing equation alone.

arXiv CS 2d ago

Symbolic Neural Generation with Applications to Lead Discovery in Drug Design

arXiv:2510.23379v2 Announce Type: replace Abstract: We investigate a relatively under-explored class of hybrid neurosymbolic models that integrate symbolic learning with neural reasoning to construct data generators meeting formal correctness criteria. In Symbolic Neural Generators (SNGs), symbolic learners examine logical specifications of feasible data from a small set of instances -- sometimes just one. Each specification in turn constrains the conditional information supplied to a...

arXiv CS 8d ago

Simultaneous Model-Based Evolution of Constants and Expression Structure in GP-GOMEA for Symbolic Regression

arXiv:2606.02236v1 Announce Type: new Abstract: Genetic programming (GP) approaches are among the state-of-the-art for symbolic regression, the task of constructing symbolic expressions that fit well with data. To find highly accurate symbolic expressions, both the expression structure and any contained real-valued constants, are important. GP-GOMEA, a modern model-based evolutionary algorithm, is one of the leading algorithms for finding accurate, yet compact expressions.

arXiv CS 8d ago

Symbolic Regression for Shared Expressions: Introducing Partial Parameter Sharing

arXiv:2601.04051v3 Announce Type: replace Abstract: Symbolic regression aims to find symbolic expressions that describe datasets. Due to its inherent interpretability, symbolic regression (SR) is a powerful paradigm for scientific discovery. Recent advances have expanded SR to describe related phenomena using a single expression with varying sets of parameters, thereby introducing a single categorical variable.

arXiv CS 6d ago

Caspar: CUDA Accelerator for Symbolic Programming with Adaptive Reordering

arXiv:2605.30583v1 Announce Type: new Abstract: We present Caspar, a library that makes the power of modern GPUs more accessible in robotics and provides a state-of-the-art nonlinear GPU solver that can be applied to a wide range of different optimization problems. Caspar bridges the gap between expressive symbolic programming in Python and high-performance GPU runtimes in C++ by automatically generating optimized CUDA kernels from symbolic expressions. Building on the SymForce library,...

arXiv CS 9d ago

BiNSGPS: Geometry Problem Solving via Bidirectional Neuro-Symbolic Interaction

Announce Type: new Abstract: Geometry problem solving poses distinct challenges in artificial intelligence. Existing approaches typically fall into two paradigms: symbolic methods, which exhibit limited adaptability, and neural methods, which are prone to hallucinations. Recent neuro-symbolic hybrids predominantly rely on a unidirectional pipeline where neural outputs are fed into solvers without feedback, making system brittle to early-stage errors.

arXiv CS 6d ago

X-ray scans uncover Nazi symbols hidden beneath postwar painting

X-ray scans uncover Nazi symbols hidden beneath postwar painting Gaby Clark Scientific Editor Andrew Zinin Lead Editor Erich Mercker (1891–1973), a painter from Munich, was quite successful in his day. Between 1933 and 1945, he painted works containing Nazi symbolism, including "Die Stätte des 9. November," which depicts the Feldherrnhalle monument in Munich commemorating the NSDAP's failed coup in 1923.

Phys.org 2d ago

Inverse Manipulation through Symbolic Planning and Residual Operator Learning

arXiv:2606.05248v1 Announce Type: new Abstract: Inverting a robotic task requires more than reversing symbolic state transitions or rewinding motor trajectories. In robot manipulation tasks, symbolic inverse plans often fail to fully restore the effects of forward executions under continuous interaction dynamics.

arXiv CS 5d ago

ANDRE: An Attention-based Neuro-symbolic Differentiable Rule Extractor for Inductive Logic Programming

arXiv:2605.04193v2 Announce Type: replace Abstract: Inductive Logic Programming (ILP) aims to learn interpretable first-order rules from data, but existing symbolic and neuro-symbolic approaches struggle to scale to noisy and probabilistic settings. Classical ILP relies on discrete combinatorial rule search and is brittle under uncertainty, while differentiable ILP methods typically depend on predefined rule templates or inaccurate fuzzy operators that suffer from vanishing gradients or poor...

arXiv CS 8d ago