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20232026
most citedBecoming self-instruct: introducing early stopping criteria for minimal instruct tuning

2 citations · 2 across the 11 of their papers we have counts for

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5 papers · 1 filter

cs.CL2026

Palmyra x6 Technical Report: An Agentic, Tool-Use Model Post-Trained via Anchored Supervised Fine-Tuning

Peng Du, Kiran Kamble, Rakshith Vasudev +5

Palmyra x6 is a large language model optimized for use with enterprise-oriented agentic tasks. The model was built by post-training a Mixture-of-Experts base model with Anchored Su…

cs.AI2026

The Harness Effect: How Orchestration Design Sets the Token Economics of Enterprise Agentic AI

Muayad Sayed Ali, Aliaksandra Novik, Anji Boddupally +29

Agentic AI development today runs on token maxing: buying capability with tokens -- longer reasoning traces, more turns, wider tool payloads, bigger replayed contexts -- so tokens…

cs.CL2026

Shorthand for Thought: Compressing LLM Reasoning via Entropy-Guided Supertokens

Zhenyu Zhao, Sander Land, Daniel M. Bikel +1

Reasoning in Large Language Models incurs significant inference-time compute, yet the token-level information structure of reasoning traces remains underexplored. We observe that r…

cs.AI2026

The Price of Agreement: Measuring LLM Sycophancy in Agentic Financial Applications

Zhenyu Zhao, Aparna Balagopalan, Adi Agrawal +3

Given the increased use of LLMs in financial systems today, it becomes important to evaluate the safety and robustness of such systems. One failure mode that LLMs frequently displa…

cs.CL2026

Accurate Failure Prediction in Agents Does Not Imply Effective Failure Prevention

Rakshith Vasudev, Melisa Russak, Dan Bikel +1

Proactive interventions by LLM critic models are often assumed to improve reliability, yet their effects at deployment time are poorly understood. We show that a binary LLM critic…