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20242026
most citedData Generation Using Large Language Models for Text Classification: An Empirical Case Study

3 citations · 5 across the 7 of their papers we have counts for

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cs.AI2026

JIVEAdapter: A Multi-Task Additive Low-Rank Adapter via Joint and Individual Variation Explained (JIVE)

Sara Abdali, Pashmina Cameron

Parameter-efficient fine-tuning adapts pretrained models at a fraction of the cost of full fine-tuning, yet most low-rank adapters are single-task and represent each weight update…

cs.LG2026

AttSVD:Prompt-Adaptive Low-Rank KV Cache Compression via Attention-Guided SVD

Sara Abdali, Jongwoo Ko, Pashmina Cameron

The key-value (KV) cache of autoregressive transformers grows linearly with context length and dominates memory at long context. Most training-free remedies evict low-importance to…

cs.AI2026

Echoverse: Deep, Evolving Environments for Training Computer-Use Agents at Scale

Yash Pandya, Sahil Gupta, Sarthak Harne +10

Computer-use agents learn from what their actions change, so training one needs applications it can act on, break and reset. The applications that matter most are login-gated and s…

cs.LG2026

Scaling Reasoning Efficiently via Relaxed On-Policy Distillation

Jongwoo Ko, Sara Abdali, Young Jin Kim +2

On-policy distillation is pivotal for transferring reasoning capabilities to capacity-constrained models, yet remains prone to instability and negative transfer. We show that on-po…

cs.AI2026

CUA-Skill: Develop Skills for Computer Using Agent

Tianyi Chen, Yinheng Li, Michael Solodko +12

Computer-Using Agents (CUAs) aim to autonomously operate computer systems to complete real-world tasks. However, existing agentic systems remain difficult to scale and lag behind h…