T-Tech

company

https://t-tech.dev

AI & ML interests

Scientific research; Natural language processing: speech analytics, search engines, dialogue systems; A family of LLMs; Speech technologies; Fraud prevention technologies; Computer vision; Recommender systems; Time series analysis

Recent Activity

kylecr4ne authored a paper 1 day ago

From Production Traffic to Post-Training: Building a Self-Hosted LLM That Covers the Corporate Request Mix

oltsy authored a paper 1 day ago

From Production Traffic to Post-Training: Building a Self-Hosted LLM That Covers the Corporate Request Mix

kenkaneki authored a paper 1 day ago

MERA Code: A Unified Framework for Evaluating Code Generation Across Tasks

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Papers

From Production Traffic to Post-Training: Building a Self-Hosted LLM That Covers the Corporate Request Mix

Qantara: Bridge-Flow Training for Multi-Paradigm JEPA Control

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t-tech 's papers 25

Submitted by

Alex Medvedev

From Production Traffic to Post-Training: Building a Self-Hosted LLM That Covers the Corporate Request Mix

t-tech

3

Qantara: Bridge-Flow Training for Multi-Paradigm JEPA Control

t-tech

Submitted by

Natyren

Rank-Then-Act: Reward-Free Control from Frame-Order Progress

t-tech

Submitted by

Nikita Balagansky

Unstable Features, Reproducible Subspaces: Understanding Seed Dependence in Sparse Autoencoders

t-tech

2

Submitted by

Nikita Balagansky

Interpreting and Steering a Text-to-Speech Language Model with Sparse Autoencoders

t-tech

2

Submitted by

Alexey Gorbatovski

Trust-Region Behavior Blending for On-Policy Distillation

t-tech

4

Learning Selective LLM Autonomy from Copilot Feedback in Enterprise Customer Support Workflows

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Submitted by

Natyren

Next Embedding Prediction Makes World Models Stronger

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Submitted by

Alexey Gorbatovski

F-GRPO: Don't Let Your Policy Learn the Obvious and Forget the Rare

t-tech

3

Submitted by

Olga Tsymboi

T-pro 2.0: An Efficient Russian Hybrid-Reasoning Model and Playground

t-tech

4

Small Vectors, Big Effects: A Mechanistic Study of RL-Induced Reasoning via Steering Vectors

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Submitted by

Daniil Gavrilov

Enhancing Vision-Language Model Training with Reinforcement Learning in Synthetic Worlds for Real-World Success

t-tech