TokenSeek: Memory Efficient Fine Tuning via Instance-Aware Token Ditching | ScienceToStartup | ScienceToStartup

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References (95)

[1]

All You Need is One: Capsule Prompt Tuning with a Single Vector

2025Yiyang Liu, J. Liang et al.

[2]

The Debate on RLVR Reasoning Capability Boundary: Shrinkage, Expansion, or Both? A Two-Stage Dynamic View

2025Xinhao Yao, Lu Yu et al.

[3]

Probabilistic Token Alignment for Large Language Model Fusion

Founder's Pitch

"TokenSeek offers a plugin for transformer models to reduce memory for fine-tuning without sacrificing performance."

LLM Fine-Tuning•Score: 3•View PDF ↗

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TokenSeek: Memory Efficient Fine Tuning via Instance-Aware Token Ditching

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References (95)

Founder's Pitch

"TokenSeek offers a plugin for transformer models to reduce memory for fine-tuning without sacrificing performance."

Commercial Viability Breakdown

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TokenSeek: Memory Efficient Fine Tuning via Instance-Aware Token Ditching

BUILDER'S SANDBOX

Build This Paper

Recommended Stack

Startup Essentials

References (95)

Founder's Pitch

"TokenSeek offers a plugin for transformer models to reduce memory for fine-tuning without sacrificing performance."

Commercial Viability Breakdown

Related Papers

Related Resources