LLM-SRBench
PulseAugur coverage of LLM-SRBench — every cluster mentioning LLM-SRBench across labs, papers, and developer communities, ranked by signal.
-
ScienceDiscovery uses tree search to autonomously refine scientific code
The openJiuwen community has developed ScienceDiscovery, a system that uses tree search to drive research product iteration (RSI), enabling programs to autonomously refine scientific code. This approach avoids retrainin…
-
LLMs improve scientific equation discovery via test-time scaling
Researchers have explored test-time scaling (TTS) for scientific equation discovery, an open-ended task where language models search for equations using data feedback. They formulated LLM-driven equation discovery as an…
-
New research explores LLM agent advancements in skill selection, autonomous driving, and compliance
Multiple research papers released on arXiv explore advancements in Large Language Model (LLM) agents, focusing on improving their capabilities and reliability. One paper introduces Best Prefix Selection (BPS) for optima…
-
LLM evolution ineffective for scientific discovery; new set-level selection method proposed
A new research paper challenges the effectiveness of iterative evolutionary approaches in scientific equation discovery using large language models (LLMs). The study found that parent-conditioned evolution yielded no si…
-
New methods enhance neural symbolic regression with LLMs and evolutionary techniques
Researchers are developing new methods for neural symbolic regression, a technique that aims to discover explicit scientific laws from data. EditSR uses a two-layer framework with a neural model and an edit-based rectif…
-
LLM-driven symbolic regression method aids scientific discovery
Researchers have developed Influence-Guided Symbolic Regression (IGSR), a novel method for scientific discovery using Large Language Models (LLMs). IGSR enhances equation discovery by generating candidate basis function…
-
New AI methods enhance symbolic regression for scientific discovery
Researchers have developed new methods for symbolic regression, a technique used to discover mathematical expressions from data. One approach, Programmatic Context Augmentation, enhances LLM-based evolutionary search by…