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ACM Transactions on Knowledge Discovery from Data 2024AmazonTexas A&MRiceLLM evaluation & benchmarks

Harnessing the Power of LLMs in Practice: A Survey on ChatGPT and Beyond

This survey guides practitioners in deploying LLMs across NLP tasks, covering model selection, data effects, use cases, biases, efficiency, and practical limitations.

Jingfeng Yang, Hongye Jin, Ruixiang Tang, Xiaotian Han and 5 more

Published Feb 28, 2024 · 503 citations

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9/21 AI panelreviewers recommend it

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AI panel: 9 of 21 reviewers recommend it
lenient 5/5
medium 4/11
strict 0/5
45%Niche pick
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NeurIPS 2026RiceBosch Center for Artificial InteInstruction tuning

LEAN: Library-Based Adaptation for Asynchronous, Federated Fine-Tuning

Erdong Hu, Yuxin Tang, Zhimin Ding, Christopher Jermaine

Paris Poster Session 3, Thu, Dec 10, 12:30 PM–2:30 PM, Paris Poster Hall · Published 2026

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69%Highly rated
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NeurIPS 2026RiceArizona StateU North Carolina at Chapel HillDepartment of Computer Science, Shanghai Artificial IntelligenceMultimodal reasoning

Do More Modalities Always Help? A Geometric Perspective on Missing-Modality Robustness

Songyuan Sui, Zhen Tan, Mohan Zhang, Rana M Khan and 2 more

Atlanta Poster Session 1, Wed, Dec 9, 10:00 AM–1:00 PM, Hall C1 · Published 2026

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3/20 AI panelreviewers recommend it

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AI panel: 3 of 20 reviewers recommend it
lenient 1/5
medium 1/10
strict 1/5
57%Worth a look
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NeurIPS 2026UCSDU California, San DiegoRiceNortheasternQuEra Computing Inc.Multi-agent LLM systems

Qubrio: High-Performance Quantum Compilation via Multi-Agent LLM Collaboration

Jixuan Ruan, Zhuo Cui, Zhengding Hu, Zhongkai Yu and 9 more

Atlanta Poster Session 4, Thu, Dec 10, 4:30 PM–7:30 PM, Hall C1 · Published 2026

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1/20 AI panelreviewers recommend it

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AI panel: 1 of 20 reviewers recommend it
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medium 0/10
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57%Worth a look
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NeurIPS 2026Carnegie MellonRiceCMU, Carnegie MellonNational University of SingaporeSchool of Computer Science, CarnEfficient attention & state-space models

Vortex: Efficient and Programmable Sparse Attention Serving

Zhuoming Chen, Xinrui Zhong, Qilong Feng, Ranajoy Sadhukhan and 4 more

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

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AI panel: 1 of 20 reviewers recommend it
lenient 1/5
medium 0/10
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45%Niche pick
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NeurIPS 2026Department of Computer Science, RiceU North Carolina at Chapel HillMichigan State University & University of North Carolina atMachine unlearning

Words Before Pixels: Selective Modality Routing for Vision-Language Model Unlearning

Laura Yao, Haochen Zhang, Jinhao Duan, Sijia Liu and 1 more

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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medium 0/10
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67%Highly rated
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NeurIPS 2026U California, BerkeleyRiceMeta / RiceUC BerkeleyIndian Institute of Technology BLong-context modeling

Long-Context Language Models Require Extreme Sparsity in Context Dimension

Prithvi Dixit, Sahil Joshi, Agniva Chowdhury, Anshumali Shrivastava and 4 more

Atlanta Poster Session 1, Wed, Dec 9, 10:00 AM–1:00 PM, Hall C1 · Published 2026

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2/20 AI panelreviewers recommend it

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AI panel: 2 of 20 reviewers recommend it
lenient 1/5
medium 0/10
strict 1/5
91%Must read
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NeurIPS 2026U California, BerkeleyRiceNVIDIAAlignment & preference optimization

Response Time Enhances Alignment with Heterogeneous Preferences

Adding response times to preference data via drift-diffusion modeling restores identifiability of average preferences among anonymous heterogeneous labelers, correcting choice-only estimation bias without tracking users.

Federico Echenique, Alireza Fallah, Baihe Huang, Michael Jordan

Atlanta Poster Session 1, Wed, Dec 9, 10:00 AM–1:00 PM, Hall C1 · 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
88%Must read
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NeurIPS 2026RiceByteDance Inc.Video generation

EntityBench: Towards Entity-Consistent Long-Range Multi-Shot Video Generation

EntityBench introduces 140-episode multi-shot video benchmark with per-shot entity schedules and three-pillar evaluation, showing explicit per-entity memory yields highest character fidelity.

Ruozhen He, Meng Wei, Ziyan Yang, Vicente Ordonez

Atlanta Poster Session 1, Wed, Dec 9, 10:00 AM–1:00 PM, Hall C1 · Published 2026 · ▲ 3 on Hugging Face

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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 8/10
strict 2/5
91%Must read
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NeurIPS 2026RiceNVIDIAFlow matching

Flow Map Denoisers: Traversing the Distortion-Perception Plane for Inverse Problems

Flow map denoisers implicitly define a one-parameter family spanning the distortion-perception tradeoff via lookahead parameter t, matching or exceeding specialized baselines across inverse problems.

Nicolas Zilberstein, Morteza Mardani, Santiago Segarra

Atlanta Poster Session 2, Wed, Dec 9, 4:30 PM–7:30 PM, Hall C1 · 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 4/5
medium 10/10
strict 3/5
71%Highly rated
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NeurIPS 2026DoshishaRiceU BaselU HelsinkiDeep learning theory

Function graph transformers universally approximate operators between function spaces

Function graph transformers lift functions to graph measures to universally approximate nonlinear operators between function spaces via standard attention and MLPs.

Takashi Furuya, S D Mis, Ivan Dokmanić, Maarten V. de Hoop and 1 more

Atlanta Poster Session 5, Fri, Dec 11, 10:00 AM–1:00 PM, Hall C1 · Published 2026

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7/20 AI panelreviewers recommend it

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AI panel: 7 of 20 reviewers recommend it
lenient 2/5
medium 3/10
strict 2/5
91%Must read
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NeurIPS 2026U VirginiaU PennsylvaniaRiceU Virginia, CharlottesvilleFacebookLLM evaluation & benchmarks

VeriContest: A Competitive-Programming Benchmark for Verifiable Code Generation

VeriContest introduces 946 competitive programming problems with verified Rust specifications and proofs, showing state-of-the-art models reach only 5.29% on end-to-end verifiable generation.

Zichen Xie, Mrigank Pawagi, Yuxin Liu, Aaditi Rai and 4 more

Atlanta Poster Session 4, Thu, Dec 10, 4:30 PM–7:30 PM, Hall C1 · Published 2026 · ▲ 1 on Hugging Face

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18/20 AI panelreviewers recommend it

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AI panel: 18 of 20 reviewers recommend it
lenient 5/5
medium 9/10
strict 4/5