23 citations · 25 across the 12 of their papers we have counts for
12 papers
Reasoning Fine-Tuning Induces Persistent Latent Policy States
Abir Harrasse, Michael Lan, Hunar Batra +2
Reasoning-specialized language models show large performance gains over base models, yet the internal changes responsible for improved multi-step reasoning remain poorly understood…
Make Mechanistic Interpretability Auditable: A Call to Develop Guidelines via Continuous Collaborative Reviewing
Michael Lan, Narmeen Fatimah Oozeer, Chaithanya Bandi +4
While mechanistic interpretability (MI) has produced important insights into neural network internals, the field has yet to establish a standardized system to audit experiments. As…
MCP-Atlas: A Large-Scale Benchmark for Tool-Use Competency with Real MCP Servers
Chaithanya Bandi, Razvan-Gabriel Dumitru, Ben Hertzberg +20
The Model Context Protocol (MCP) is emerging as a standard interface through which large language model (LLM) agents discover and invoke external tools. However, existing MCP evalu…
ResearchRubrics: A Benchmark of Prompts and Rubrics For Evaluating Deep Research Agents
Manasi Sharma, Chen Bo Calvin Zhang, Chaithanya Bandi +13
Deep Research (DR) is an emerging agent application that leverages large language models (LLMs) to address open-ended queries. It requires the integration of several capabilities,…
Position: Require Frontier AI Labs To Release Small "Analog" Models
Shriyash Upadhyay, Chaithanya Bandi, Narmeen Oozeer +1
Recent proposals for regulating frontier AI models have sparked concerns about the cost of safety regulation, and most such regulations have been shelved due to the safety-innovati…
Beyond Monoliths: Expert Orchestration for More Capable, Democratic, and Safe Language Models
Philip Quirke, Narmeen Oozeer, Chaithanya Bandi +8
This position paper argues that the prevailing trajectory toward ever larger, more expensive generalist foundation models controlled by a handful of companies limits innovation and…
REL: Working out is all you need
Toby Simonds, Jey Han Lau, Chaithanya Bandi
Recent developments, particularly OpenAI's O1 model, have demonstrated the remarkable potential of Large Language Models (LLMs) for complex reasoning tasks. Through analysis of O1'…
Debate, Deliberate, Decide (D3): A Cost-Aware Adversarial Framework for Reliable and Interpretable LLM Evaluation
Abir Harrasse, Chaithanya Bandi, Hari Bandi
The evaluation of Large Language Models (LLMs) remains challenging due to inconsistency, bias, and the absence of transparent decision criteria in automated judging. We present Deb…
Supply Function Equilibrium in Networked Electricity Markets
YuanzhangXiao, ChaithanyaBandi, Ermin Wei
We study deregulated power markets with strategic power suppliers. In deregulated markets, each supplier submits its supply function (i.e., the amount of electricity it is willing…
An Application of Newsboy Problem in Supply Chain Optimisation of Online Fashion E-Commerce
Chandramouli Kamanchi, Gopinath Ashok Kumar, Nachiappan Sundaram +2
We describe a supply chain optimization model deployed in an online fashion e-commerce company in India called Myntra. Our model is simple, elegant and easy to put into service. Th…
Sustainable Inventory with Robust Periodic-Affine Policies and Application to Medical Supply Chains
Chaithanya Bandi, Eojin Han, Omid Nohadani
We introduce a new class of adaptive policies called periodic-affine policies, that allows a decision maker to optimally manage and control large-scale newsvendor networks in the p…
Robust Optimization for Electricity Generation
Chaithanya Bandi, Krishnamurthy Dvijotham, David Morton +1
We consider a robust optimization problem in an electric power system under uncertain demand and availability of renewable energy resources. Solving the deterministic alternating c…