53 citations · 98 across the 21 of their papers we have counts for
8 papers · 1 filter
R2V Agent: Teaching SLMs When to Ask for Help
Raghu Vamshi Hemadri, Humaira Firdowse Mohammed, Rishabh Maheshwary +5
Efficient agentic systems should incur expensive frontier-model costs only on decisions where a cheaper local model is likely to fail. Existing LLM cascades usually route whole que…
Do Enterprise Systems Need Learned World Models? The Importance of Context to Infer Dynamics
Jishnu Sethumadhavan Nair, Patrice Bechard, Rishabh Maheshwary +14
World models enable agents to anticipate the effects of their actions by internalizing environment dynamics. In enterprise systems, however, these dynamics are often defined by ten…
EVA-Bench: A New End-to-end Framework for Evaluating Voice Agents
Tara Bogavelli, Gabrielle Gauthier Melançon, Katrina Stankiewicz +10
Voice agents are increasingly deployed across enterprise applications. However, no existing benchmark jointly addresses realistic conversation simulation and comprehensive voice-sp…
Super Apriel: One Checkpoint, Many Speeds
SLAM Labs, :, Oleksiy Ostapenko +13
We release Super Apriel, a 15B-parameter supernet in which every decoder layer provides four trained mixer choices -- Full Attention (FA), Sliding Window Attention (SWA), Kimi Delt…
Terminal Agents Suffice for Enterprise Automation
Patrice Bechard, Orlando Marquez Ayala, Emily Chen +5
There has been growing interest in building agents that can interact with digital platforms to execute meaningful enterprise tasks autonomously. Among the approaches explored are t…
Ego2Web: A Web Agent Benchmark Grounded in Egocentric Videos
Shoubin Yu, Lei Shu, Antoine Yang +6
Multimodal AI agents are increasingly automating complex real-world workflows that involve online web execution. However, current web-agent benchmarks suffer from a critical limita…
EnterpriseOps-Gym: Environments and Evaluations for Stateful Agentic Planning and Tool Use in Enterprise Settings
Shiva Krishna Reddy Malay, Shravan Nayak, Jishnu Sethumadhavan Nair +6
Large language models are shifting from passive information providers to active agents intended for complex workflows. However, their deployment as reliable AI workers in enterpris…
AprielGuard
Jaykumar Kasundra, Anjaneya Praharaj, Sourabh Surana +11
Safeguarding large language models (LLMs) against unsafe or adversarial behavior is critical as they are increasingly deployed in conversational and agentic settings. Existing mode…