collaborators

9 papers

cs.CL2026

Mind the Cap: Output-Budget Regimes Change the Measured Multilingual Reasoning Gap

Ankit Goyal, Jaideep Ray

Multilingual evaluations report accuracy at a single output-token cap, but languages need different numbers of tokens to express the same content, so the cap is a hidden experiment…

cs.CL2026

From Agent Failures to Text Policies: What Works and What Breaks

Jaideep Ray, Ankit Goyal

TextGrad improves language-model systems by revising text from feedback. Its core thesis is that natural-language feedback can act as a gradient for optimizing text components with…

cs.SE2026

Structured Feedback Improves Repair in an LLM Agent Loop

Jaideep Ray, Ankit Goyal

The paper presents VeriHarness, a code‑controlled loop that lets external validators give structured feedback (failure location, observed value, admissible alternatives) to LLM age…

cs.RO2026

RoboLab: A High-Fidelity Simulation Benchmark for Analysis of Task Generalist Policies

Jenai Xuning Yang, Xuning Yang, Rishit Dagli +6

The pursuit of general-purpose robotics has yielded impressive foundation models, yet simulation-based benchmarking remains a bottleneck due to rapid performance saturation and a l…

cs.RO2025

OG-VLA: Orthographic Image Generation for 3D-Aware Vision-Language Action Model

Ishika Singh, Ankit Goyal, Stan Birchfield +3

We introduce OG-VLA, a novel architecture and learning framework that combines the generalization strengths of Vision Language Action models (VLAs) with the robustness of 3D-aware…

cs.RO2025

VLA-0: Building State-of-the-Art VLAs with Zero Modification

Ankit Goyal, Hugo Hadfield, Xuning Yang +2

Vision-Language-Action models (VLAs) hold immense promise for enabling generalist robot manipulation. However, the best way to build them remains an open question. Current approach…