5 papers
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…
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…
GRAFT: GRaPH and Table Reasoning for Textual Alignment -- A Benchmark for Structured Instruction Following and Visual Reasoning
Abhigya Verma, Sriram Puttagunta, Seganrasan Subramanian +1
GRAFT is a structured multimodal benchmark designed to probe how well LLMs handle instruction following, visual reasoning, and tasks requiring tight visual textual alignment. The d…
FABRIC: Framework for Agent-Based Realistic Intelligence Creation
Abhigya Verma, Seganrasan Subramanian, Nandhakumar Kandasamy +1
Large language models (LLMs) are increasingly deployed as agents, expected to decompose goals, invoke tools, and verify results in dynamic environments. Realizing these capabilitie…
Modular Techniques for Synthetic Long-Context Data Generation in Language Model Training and Evaluation
Seganrasan Subramanian, Abhigya Verma
The ability of large language models (LLMs) to process and reason over long textual inputs is critical for a wide range of real-world applications. However, progress in this area i…