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Showing papers from MIT - Massachusetts Institute of Technology Show all papers

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NeurIPS 2026MIT - Massachusetts Institute ofAWS AI LabsUT-AustinAWSAmazonRL for LLMs

MURPHY: Feedback-Aware GRPO with Retrospective Credit Assignment for Multi-Turn Code Generation

MURPHY extends GRPO to multi-turn code generation via feedback-conditioned rollout trees with retrospective credit assignment, achieving up to 6% absolute pass@1 gains over prior methods.

Chanakya Ekbote, Vijay Lingam, Sujay Sanghavi, Luke Huan and 3 more

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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15/20 AI panelreviewers recommend it

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AI panel: 15 of 20 reviewers recommend it
lenient 5/5
medium 9/10
strict 1/5
91%Must read
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NeurIPS 2026KU LeuvenDepartment of Electrical EngineeKatholieke Universiteit LeuvenKULMassachusetts Institute of TechnBiosignals & wearables

NeuroAtlas: Benchmarking Foundation Models for Clinical EEG and Brain-Computer Interfaces

NeuroAtlas benchmarks EEG foundation models across 42 datasets and finds they largely match generic time-series models without delivering unified clinical EEG performance.

Konstantinos Kontras, Trui Osselaer, Stylianos G Mouslech, Angeliki I. Karaiskou and 11 more

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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17/20 AI panelreviewers recommend it

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AI panel: 17 of 20 reviewers recommend it
lenient 5/5
medium 9/10
strict 3/5
78%Highly rated
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NeurIPS 2026U Texas at AustinMIT - Massachusetts Institute ofHarvardU California, BerkeleyU Texas, AustinLLM reasoning & chain of thought

Interleaved Head Attention

Interleaved Head Attention mixes attention heads via pseudo-heads to enable cross-head reasoning, cutting parameters on synthetic tasks and improving retrieval and math benchmarks over standard multi-head attention.

Sai Surya Duvvuri, Chanakya Ekbote, Rachit Bansal, Rishabh Tiwari and 5 more

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026 · ▲ 2 on Hugging Face

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11/20 AI panelreviewers recommend it

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AI panel: 11 of 20 reviewers recommend it
lenient 5/5
medium 6/10
strict 0/5