TCA-SIR: Learning Target-Conditioned Abstractions for Scientific Inspiration Retrieval

arXiv:2607.28498 · cs.IR, cs.AI, cs.CL · Submitted 2026-07-30 · Read on arXiv

Yuto Suzuki, Farnoush Banaei-Kashani

cs.IR, cs.AI, cs.CL

Submitted: 2026-07-30

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Abstraction — 106× in this paper · explained in 1 episode
• Transferability — 21× in this paper · explained in 5 episodes
• Core — 20× in this paper · explained in 2 episodes
• Papers — 17× in this paper · explained in 3 episodes
• Scientific Inspiration Retrieval — 13× in this paper
• Ablation — 8× in this paper · explained in 1 episode
• Accuracy — 8× in this paper · explained in 1 episode
• Composition — 6× in this paper · explained in 2 episodes
• Adaptive Optics — 3× in this paper
• Benchmark — 3× in this paper · explained in 2 episodes
• Calibration — 3× in this paper · explained in 9 episodes
• Embeddings — 3× in this paper · explained in 2 episodes
• Fine-Tuning — 3× in this paper · explained in 5 episodes
• Gradient Flow — 3× in this paper · explained in 2 episodes
• Loss Function — 3× in this paper · explained in 2 episodes
• Composite Loss Function — 2× in this paper · explained in 4 episodes
• Interface Engineering — 2× in this paper · explained in 2 episodes
• Trace — 2× in this paper · explained in 2 episodes
• AI Agents — 1× in this paper · explained in 2 episodes
• Ablation Study — 1× in this paper · explained in 3 episodes
• Adaptive Optics (AO) — 1× in this paper · explained in 3 episodes
• Agentic System — 1× in this paper · explained in 2 episodes
• Artificial Intelligence (AI) — 1× in this paper · explained in 2 episodes
• Benchmarking — 1× in this paper · explained in 4 episodes
• Clustering — 1× in this paper · explained in 2 episodes
• Consistency — 1× in this paper · explained in 3 episodes
• Cosine Similarity — 1× in this paper · explained in 3 episodes
• Decoder — 1× in this paper · explained in 2 episodes
• Distillation — 1× in this paper · explained in 2 episodes
• Failure Modes — 1× in this paper · explained in 3 episodes
• Generative AI — 1× in this paper · explained in 2 episodes
• Generative Model — 1× in this paper · explained in 2 episodes
• Generator — 1× in this paper · explained in 2 episodes
• Harness — 1× in this paper · explained in 2 episodes
• Inductive Bias — 1× in this paper · explained in 3 episodes
• Interpretability — 1× in this paper · explained in 15 episodes
• Multi-objective Optimization — 1× in this paper · explained in 5 episodes
• Representation Learning — 1× in this paper · explained in 3 episodes
• Scoring Function — 1× in this paper · explained in 2 episodes
• Task Decomposition — 1× in this paper · explained in 2 episodes
• Training Objective — 1× in this paper · explained in 3 episodes
• Transformer — 1× in this paper · explained in 2 episodes
• Transformers — 1× in this paper · explained in 2 episodes
• Unified Framework — 1× in this paper · explained in 6 episodes
• Verification — 1× in this paper · explained in 2 episodes

Sources

• Automating Exploratory Proteomics Research via Language Models
• AbstRaL: Augmenting LLMs' Reasoning by Reinforcing Abstract Thinking
• LLMs can Realize Combinatorial Creativity: Generating Creative Ideas via LLMs for Scientific Research
• Sparking Scientific Creativity via LLM-Driven Interdisciplinary Inspiration
• The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery
• AlphaEvolve: A coding agent for scientific and algorithmic discovery
• RLAD: Training LLMs to Discover Abstractions for Solving Reasoning Problems
• Towards Autonomous Hypothesis Verification via Language Models with Minimal Guidance
• From AI for Science to Agentic Science: A Survey on Autonomous Scientific Discovery
• The AI Scientist-v2: Workshop-Level Automated Scientific Discovery via Agentic Tree Search

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