16 papers
The ACUTE Protocol: Operationalizing Language Model Activations for Better Calibration, Utility, and Trust
Nishant Subramani, Palash Goyal, Yiwen Song +4
As language models improve and become increasingly deployed to solve a variety of tasks, trustworthiness becomes essential. Calibration is a good proxy for trust: well-calibrated c…
ScientistOne: Towards Human-Level Autonomous Research via Chain-of-Evidence
Rui Meng, Bhavana Dalvi Mishra, Jiefeng Chen +10
Autonomous research agents produce competitive solutions and professional-looking manuscripts, yet their outputs contain verifiability failures undetectable by surface-level evalua…
Nexus : An Agentic Framework for Time Series Forecasting
Sarkar Snigdha Sarathi Das, Palash Goyal, Mihir Parmar +6
Time series forecasting is not just numerical extrapolation, but often requires reasoning with unstructured contextual data such as news or events. While specialized Time Series Fo…
LEAF: A Living Benchmark for Event-Augmented Forecasting
Mingtian Tan, Mihir Parmar, Palash Goyal +5
Large Language Models (LLMs) are increasingly applied to forecasting. To evaluate this capability while mitigating pre-training data contamination, several living benchmarks have b…
Reasoning-Aware Training for Time Series Forecasting
Md Atik Ahamed, Mihir Parmar, Palash Goyal +4
Time Series Foundation Models (TSFMs) excel at numerical forecasting but operate as black boxes lacking qualitative reasoning. Conversely, applying LLMs directly to temporal data i…
ScholarPeer: A Context-Aware Multi-Agent Framework for Automated Peer Review
Palash Goyal, Mihir Parmar, Yiwen Song +3
The exponential growth of machine learning submissions has strained the traditional peer review process, resulting in slow feedback loops for authors and an immense burden on revie…