21 citations · 33 across the 16 of their papers we have counts for
6 papers · 1 filter
MURPHY: Feedback-Aware GRPO with Retrospective Credit Assignment for Multi-Turn Code Generation
Chanakya Ekbote, Vijay Lingam, Sujay Sanghavi +4
Reinforcement Learning with Verifiable Rewards (RLVR) has become a standard recipe for post-training LLMs on reasoning tasks, with Group Relative Policy Optimization (GRPO) emergin…
What One Cannot, Two Can: Two-Layer Transformers Provably Represent Induction Heads on Any-Order Markov Chains
Chanakya Ekbote, Marco Bondaschi, Nived Rajaraman +4
In-context learning (ICL) is a hallmark capability of transformers, through which trained models learn to adapt to new tasks by leveraging information from the input context. Prior…
PuzzleWorld: A Benchmark for Multimodal, Open-Ended Reasoning in Puzzlehunts
Hengzhi Li, Justin Zhang, Brendon Jiang +9
Puzzlehunts are a genre of complex, multi-step puzzles lacking well-defined problem definitions. In contrast to conventional reasoning benchmarks consisting of tasks with clear ins…
QoQ-Med: Building Multimodal Clinical Foundation Models with Domain-Aware GRPO Training
Wei Dai, Peilin Chen, Chanakya Ekbote +1
Clinical decision-making routinely demands reasoning over heterogeneous data, yet existing multimodal language models (MLLMs) remain largely vision-centric and fail to generalize a…
TAMP: Token-Adaptive Layerwise Pruning in Multimodal Large Language Models
Jaewoo Lee, Keyang Xuan, Chanakya Ekbote +3
Multimodal Large Language Models (MLLMs) have shown remarkable versatility in understanding diverse multimodal data and tasks. However, these capabilities come with an increased mo…
Understanding the Emergence of Multimodal Representation Alignment
Megan Tjandrasuwita, Chanakya Ekbote, Liu Ziyin +1
Multimodal representation learning is fundamentally about transforming incomparable modalities into comparable representations. While prior research primarily focused on explicitly…