Good Papers

Showing papers from Google Research Show all papers

45%Niche pick
?Niche pickVote to see the score
NeurIPS 2026GoogleGoogle ResearchDukeControllable generation

Sample-Efficient Optimization over Generative Priors via Coarse Learnability

Pranjal Awasthi, Sreenivas Gollapudi, Ravi Kumar, Kamesh Munagala

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
0/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 0 of 20 reviewers recommend it
lenient 0/5
medium 0/10
strict 0/5
45%Niche pick
?Niche pickVote to see the score
NeurIPS 2026PrincetonGoogleGoogle researchVirginia TechGoogle ResearchData attribution

A Computational Perspective to Data Ablation Experiments

Jiachen (Tianhao) Wang, Lin Chen, Mohammadhossein Bateni, Ruoxi Jia and 2 more

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

– ReadersNo votes yet
0/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 0 of 20 reviewers recommend it
lenient 0/5
medium 0/10
strict 0/5
45%Niche pick
?Niche pickVote to see the score
NeurIPS 2026YaleGoogleGoogle ResearchLLM reasoning & chain of thought

Programmatic Reasoning with Structural Schema: A Unified Framework for Multi-Table Inference

Jialin Chen, Brandon Mayer, Michael Galkin, Sami Abu-El-Haija and 2 more

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
0/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 0 of 20 reviewers recommend it
lenient 0/5
medium 0/10
strict 0/5
57%Worth a look
?Worth a lookVote to see the score
NeurIPS 2026GoogleU Southern CaliforniaGoogle ResearchUC San Diego / MilaRepresentation & contrastive learning

A Foundational Model System for Datacenter Machine Repairs

Yuanlin Wen, Elan S Markowitz, Zubo Gu, Sami Abu-El-Haija and 10 more

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

– ReadersNo votes yet
1/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 1 of 20 reviewers recommend it
lenient 1/5
medium 0/10
strict 0/5
67%Highly rated
?Highly ratedVote to see the score
NeurIPS 2026Reflection.aiU CambridgeGoogle DeepMindGoogle ResearchGoogle DeepMind & UCLWeb & GUI agents

A Subgoal-driven RL Framework for Improving Long-Horizon Web Agents

Taiyi Wang, Sian Gooding, Florian Hartmann, Oriana Riva and 1 more

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
2/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 2 of 20 reviewers recommend it
lenient 2/5
medium 0/10
strict 0/5
45%Niche pick
?Niche pickVote to see the score
NeurIPS 2026U Illinois Urbana-ChampaignUIUCGoogle ResearchU Illinois at Urbana-ChampaignU Illinois, Urbana ChampaignDeep RL

RL-Inf: Tracking Non-local Training Data Influence for Online Reinforcement Learning

Shixuan Liu, Cheng Tang, Yuzheng Hu, Fan Wu and 2 more

Atlanta Poster Session 2, Wed, Dec 9, 4:30 PM–7:30 PM, Hall C1 · Published 2026

– ReadersNo votes yet
0/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 0 of 20 reviewers recommend it
lenient 0/5
medium 0/10
strict 0/5
57%Worth a look
?Worth a lookVote to see the score
NeurIPS 2026UC BerkeleyMicrosoft ResearchU California, BerkeleyOpenAIEECS, UC BerkeleyEfficient inference & serving

SPECS: Faster Test-Time Scaling through Speculative Drafts and Dynamic Switching

Mert Cemri, Nived Rajaraman, Rishabh Tiwari, Xiaoxuan Liu and 5 more

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
1/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 1 of 20 reviewers recommend it
lenient 1/5
medium 0/10
strict 0/5
57%Worth a look
?Worth a lookVote to see the score
NeurIPS 2026GoogleGoogle ResearchElectrical Engineering & ComVQA & captioning

Mind the Gap: Dataset and Fine-grained Evaluation for Inline Audio Descriptions

Subhashini Venugopalan, Yingwen Tan, Taylor Roper, Jimmy Tobin and 4 more

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
1/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 1 of 20 reviewers recommend it
lenient 1/5
medium 0/10
strict 0/5
45%Niche pick
?Niche pickVote to see the score
NeurIPS 2026Google ResearchLearning theory

Majority-of-Three is an Optimal PAC Learner

Grigoris Velegkas

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

– ReadersNo votes yet
0/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 0 of 20 reviewers recommend it
lenient 0/5
medium 0/10
strict 0/5
45%Niche pick
?Niche pickVote to see the score
NeurIPS 2026Google ResearchGoogle Research & Courant InResearch Scientist, Google ReseaDeep RL

SAMPPO: Structure-Aware Mirror Proximal Policy Optimization

Corinna Cortes, Mehryar Mohri, Yutao Zhong

Atlanta Poster Session 6, Fri, Dec 11, 4:30 PM–7:30 PM, Hall C1 · Published 2026

– ReadersNo votes yet
0/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 0 of 20 reviewers recommend it
lenient 0/5
medium 0/10
strict 0/5
45%Niche pick
?Niche pickVote to see the score
NeurIPS 2026Google ResearchGoogle Google ResearchRL for LLMs

MaxIM: Maximally Informative Incremental Summarization via Reinforcement Learning

Jihwan Jeong, Guy Tennenholtz, Yinlam Chow, Chih-wei Hsu and 1 more

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

– ReadersNo votes yet
0/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 0 of 20 reviewers recommend it
lenient 0/5
medium 0/10
strict 0/5
45%Niche pick
?Niche pickVote to see the score
NeurIPS 2026Google DeepMindGoogle ResearchGoogleHPI f. Digit. Engin. GGMBHMachine unlearning

We Should Distinguish Unlearning From Untraining

Eleni Triantafillou, Imtiaz Humayun, Mónica Ribero, Alexander Turner and 2 more

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

– ReadersNo votes yet
0/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 0 of 20 reviewers recommend it
lenient 0/5
medium 0/10
strict 0/5
45%Niche pick
?Niche pickVote to see the score
NeurIPS 2026SapienzaSapienza University of RomeGoogleGoogle ResearchSapienza, University of RomeRecommender systems

Beyond the Full Slate: Evaluating MNL Algorithms on All Slates

Flavio Chierichetti, Mirko Giacchini, Ravi Kumar, Silvio Lattanzi and 3 more

Atlanta Poster Session 2, Wed, Dec 9, 4:30 PM–7:30 PM, Hall C1 · Published 2026

– ReadersNo votes yet
0/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 0 of 20 reviewers recommend it
lenient 0/5
medium 0/10
strict 0/5
45%Niche pick
?Niche pickVote to see the score
NeurIPS 2026U MarylandU Maryland, College ParkGoogle ResearchGraph neural networks

Efficient Dynamic Algorithms for Graph Neural Networks with Non-Linearity

Kiarash Banihashem, MohammadTaghi Hajiaghayi, Mahdi JafariRaviz, Silvio Lattanzi and 1 more

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

– ReadersNo votes yet
0/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 0 of 20 reviewers recommend it
lenient 0/5
medium 0/10
strict 0/5
80%Must read
?Must readVote to see the score
NeurIPS 2026GoogleGoogle ResearchComputational neuroscience

Discovering Mechanistic Models of Neural Activity: System Identification in an in Silico Zebrafish

LLM-based tree search discovers predictive zebrafish neural models that outperform forecasting baselines, though structural priors are needed to prevent shortcut exploitation and ensure mechanistic recovery.

Jan-Matthis Lueckmann, Viren Jain, Michal Januszewski

Paris Poster Session 6, Fri, Dec 11, 2:30 PM–4:30 PM, Paris Poster Hall · Published 2026

– ReadersNo votes yet
12/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 12 of 20 reviewers recommend it
lenient 5/5
medium 6/10
strict 1/5
80%Must read
?Must readVote to see the score
NeurIPS 2026NortheasternU Southern CaliforniaGoogle ResearchProbing & representation analysis

Geometric Signatures of Reasoning: A Spectral Perspective on Task Hardness

Reasoning trajectories are discrete hidden-state curves whose spectral flatness measures task hardness and whose kinematics predict correctness early.

Aria Masoomi, Mahsa Bazzaz, Adel Javanmard, Vahab Mirrokni

Atlanta Poster Session 6, Fri, Dec 11, 4:30 PM–7:30 PM, Hall C1 · Published 2026

– ReadersNo votes yet
12/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 12 of 20 reviewers recommend it
lenient 5/5
medium 6/10
strict 1/5
89%Must read
?Must readVote to see the score
NeurIPS 2026Harvard University, HarvardHarvardCarnegie MellonGoogle DeepMindGoogle ResearchGenomics & single-cell

How Post-Training Shapes Biological Reasoning Models

Continued pre-training aligns biological language, supervised fine-tuning improves in-domain but harms out-of-domain reasoning, and reinforcement learning recovers generalization when rewards align.

Lukas Fesser, Hanlin Zhang, Michelle M Li, Eric Wang and 4 more

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026 · ▲ 3 on Hugging Face

– ReadersNo votes yet
16/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 16 of 20 reviewers recommend it
lenient 5/5
medium 7/10
strict 4/5
80%Must read
?Must readVote to see the score
NeurIPS 2026U ArkansasU Arkansas - FayettevilleGoogle ResearchU LiverpoolDFKI & Max Planck Research SVision-language models

OmniSpace: Efficient Geometry Awareness for Autonomous Vehicles MLLMs

OmniSpace improves autonomous vehicle MLLM spatial reasoning via camera pose injection, multi-view epipolar attention, and 3D geometric distillation without auxiliary 3D models, surpassing existing methods across planning, risk detection, and language benchmarks.

Anh Hao Vo, Phu Loc Nguyen, Khoa Vo, Sieu Tran and 6 more

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
12/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 12 of 20 reviewers recommend it
lenient 5/5
medium 7/10
strict 0/5
88%Must read
?Must readVote to see the score
NeurIPS 2026GoogleGoogle, Tel AvivTechnionGoogle ResearchLLM evaluation & benchmarks

Controllable User Simulation

Controllable user simulation is formalized as causal inference, proving supervised fine-tuning injects look-ahead bias causing geometric variance explosion and controllability collapse, with proposed mitigations restoring consistency and robust generalization.

Guy Tennenholtz, Ofer Meshi, Amir Globerson, Uri Shalit and 2 more

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

– ReadersNo votes yet
15/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 15 of 20 reviewers recommend it
lenient 4/5
medium 7/10
strict 4/5
74%Highly rated
?Highly ratedVote to see the score
NeurIPS 2026SpotlightGoogle ResearchAGH University, PolandOptimization

Polynomial-Time Algorithm for Thiele Voting Rules with Voter Interval Preferences

A polynomial-time algorithm computes optimal Thiele committees for voter-interval preferences via a concavity theorem and Lagrangian relaxation.

Pasin Manurangsi, Krzysztof Sornat

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
9/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 9 of 20 reviewers recommend it
lenient 1/5
medium 5/10
strict 3/5
Show 20 more papers