collaborators

7 papers

cs.CL2026

MENTIS: What Belief Changes Under Alignment? Measuring Multi-Scale Latent Torsion in Language Models

Partha Pratim Saha, Samarth Raina, Mayur Parvatikar +4

Preference alignment has substantially improved the observable behavior of large language models, yet it remains unclear what alignment changes internally. Aligned systems still fa…

cs.LG2026

SPHERICAL KV: Angle-Domain Attention and Rate-Distortion Retention for Efficient Long-Context Inference

Anay Chauhan, Gurucharan Marthi Krishna Kumar, Arion Das +4

Long-context inference is increasingly constrained by the KV cache: resident memory grows with context length, and decoding becomes limited by repeated High Bandwidth Memory (HBM)…

cs.MA2026

Safe Equilibrium Policy Optimization for Strategic Agent Policies

Karthika Arumugam, Kiran Kumar Manku, Amit Dhanda

Language models fine-tuned with reinforcement learning typically optimize for task reward, ignoring multi-agent strategic structure. Because these agents condition on natural langu…

cs.AI2026

Chart-RL: Policy Optimization Reinforcement Learning for Enhanced Visual Reasoning in Chart Question Answering with Vision Language Models

Yunfei Bai, Amit Dhanda, Shekhar Jain

The recent advancements in Vision Language Models (VLMs) have demonstrated progress toward true intelligence requiring robust reasoning capabilities. Beyond pattern recognition, li…

cs.AI2026

DeltaLogic: Minimal Premise Edits Reveal Belief-Revision Failures in Logical Reasoning Models

Amit Dhanda

Reasoning benchmarks typically evaluate whether a model derives the correct answer from a fixed premise set, but they under-measure a closely related capability that matters in dyn…

cs.LG2026

SPINAL -- Scaling-law and Preference Integration in Neural Alignment Layers

Arion Das, Partha Pratim Saha, Amit Dhanda +3

Direct Preference Optimization (DPO) is a principled, scalable alternative to RLHF for aligning large language models from pairwise preferences, but its internal geometric footprin…