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Sambit Sahu

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#artificial intelligence Preprint Oct 2026

AdaGuard: Enhancing Safety and Policy Compliance with Reasoning-Enabled LLM-As-A-Judge Guardrails

Enterprise generative AI applications require robust safety mechanisms that can accommodate diverse risk postures, evolving policies, and varying latency constraints. Current guardrail solutions often suffer from rigidity, relying on fixed policy sets and offering limited transparency or reasoning flexibility. We prese...

Melissa Kazemi Rad, Si-Hui Dai, Isha Slavin et al. · 0 citations
Preprint Aug 2026

StreamHear: Domain-Adapted Pseudo-Labeling for Semi-Supervised Streaming Speech Recognition

Streaming automatic speech recognition (ASR) underperforms on domain-shifted target audio, where labeled in-domain data is costly to prepare while unlabeled audio is abundant. We present StreamHear, a semi-supervised pipeline that adapts a pretrained streaming student by fine-tuning an offline transducer teacher on the...

Zefang Liu, Chenyang Zhu, Sangwoo Cho et al. · 0 citations
#artificial intelligence Preprint Sep 2026

When Load-Balancing Goes Too Far: Expert Pruning in Over-Dispersed Mixture-of-Experts Models

The results indicate that over-dispersed routing is a qualitatively distinct pruning regime in which standard assumptions fail, and that recognizing it is a prerequisite for principled expert pruning of load-balanced MoE models.

Berkcan Kapusuzoglu, Connor Pryor, Sangwoo Cho et al. · 0 citations
#artificial intelligence Preprint Sep 2026

The Rise of Verbal Reinforcement Learning

This taxonomy shows how verbal reinforcement is reshaping agent development, while also defining the challenges and opportunities for building more capable and aligned agents.

Kshitij Tayal, Arun Sharma, Genta Indra Winata et al. · 0 citations
Jul 2026

Structured Thoughts For Improved Reasoning And Context Pruning

This work introduces Structured Thoughts, a framework that organizes reasoning into alternating blocks and blocks that captures exploratory scratch work, while the distilled conclusion of that step contains the distilled conclusion of that step.

Zain Sarwar, Supriyo Chakraborty, Berkcan Kapusuzoglu et al. · 0 citations
#human-computer interacti... Preprint Aug 2026

AREAs-Lab: An Interactive Environment for AI-driven Requirement Elicitation for AI Systems

Building effective AI systems increasingly depends on writing high-quality task requirements, yet users often struggle to articulate the constraints, preferences, and edge cases that determine success. This problem is especially acute in AI development, where behavior is shaped not only by human expectations but also b...

Pengshan Cai, Zi-Hao Zhang, Ting Jin et al. · 0 citations
Preprint Aug 2026

Efficient Reinforcement Learning for Long-Horizon Tool-Use Agentic Tasks

SINKFLEX-RL, a modular training system for RL in dual-control tool-use environments that combines a Gymnasium-compatible environment wrapper, a VERL-style rollout dataflow, group-relative policy optimization without a separate value model, and a sink-aware FlexAttention path designed to preserve model-specific sink sca...

Zelei Cheng, Amritansh Mishra, Sambit Sahu et al. · 0 citations

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